chore: widen click dependency to >=8.1.7,<9

Relaxes the click pin from ~=8.1.7 (which caps at <8.2.0) to >=8.1.7,<9.
This allows enterprise customers with InfoSec requirements for click 8.3.x
to install CrewAI without dependency resolution failures.

Click 8.1→8.3 has no breaking changes for our CLI decorator usage.

Affected files:
- lib/crewai/pyproject.toml
- lib/cli/pyproject.toml
- lib/devtools/pyproject.toml

.github/workflows/vulnerability-scan.yml

@@ -71,7 +71,8 @@ jobs:
             --ignore-vuln PYSEC-2025-215 \
             --ignore-vuln PYSEC-2025-216 \
             --ignore-vuln PYSEC-2025-217 \
-            --ignore-vuln PYSEC-2025-218
+            --ignore-vuln PYSEC-2025-218 \
+            --ignore-vuln GHSA-f4j7-r4q5-qw2c
         # Ignored CVEs:
         #   PYSEC-2024-277      - joblib 1.5.3: disputed; NumpyArrayWrapper only used with trusted caches
         #   PYSEC-2026-89       - markdown 3.10.2: DoS via malformed HTML; fix 3.8.1 — already past, advisory range is stale
@@ -81,6 +82,9 @@ jobs:
         #   PYSEC-2025-189..197 - torch 2.11.0: memory-corruption/DoS in functions only reachable via untrusted models; no fix available
         #   PYSEC-2025-210, PYSEC-2026-139 - torch 2.11.0: profiler/deserialization issues; no fix available
         #   PYSEC-2025-211..218 - transformers 5.5.4: deserialization/code injection via malicious model checkpoints; no fix available
+        #   GHSA-f4j7-r4q5-qw2c - chromadb 1.1.1 (CVE-2026-45829): pre-auth RCE via /api/v2/tenants/{tenant}/databases/{db}/collections when trust_remote_code=true.
+        #                         Advisory: vulnerable >=1.0.0,<=1.5.9, firstPatchedVersion=none. We only use chromadb.PersistentClient (lib/crewai/src/crewai/rag/chromadb/factory.py)
+        #                         and chromadb.utils.embedding_functions; the chromadb HTTP server is never started, so the vulnerable route is not exposed.
         continue-on-error: true
 
       - name: Display results

.pre-commit-config.yaml

@@ -28,7 +28,34 @@ repos:
     hooks:
       - id: pip-audit
         name: pip-audit
-        entry: bash -c 'source .venv/bin/activate && uv run pip-audit --skip-editable --ignore-vuln CVE-2026-3219' --
+        # Keep this ignore list in sync with .github/workflows/vulnerability-scan.yml.
+        entry: >-
+          bash -c 'source .venv/bin/activate && uv run pip-audit --skip-editable
+          --ignore-vuln PYSEC-2024-277
+          --ignore-vuln PYSEC-2026-89
+          --ignore-vuln PYSEC-2026-97
+          --ignore-vuln PYSEC-2025-148
+          --ignore-vuln PYSEC-2025-183
+          --ignore-vuln PYSEC-2025-189
+          --ignore-vuln PYSEC-2025-190
+          --ignore-vuln PYSEC-2025-191
+          --ignore-vuln PYSEC-2025-192
+          --ignore-vuln PYSEC-2025-193
+          --ignore-vuln PYSEC-2025-194
+          --ignore-vuln PYSEC-2025-195
+          --ignore-vuln PYSEC-2025-196
+          --ignore-vuln PYSEC-2025-197
+          --ignore-vuln PYSEC-2025-210
+          --ignore-vuln PYSEC-2026-139
+          --ignore-vuln PYSEC-2025-211
+          --ignore-vuln PYSEC-2025-212
+          --ignore-vuln PYSEC-2025-213
+          --ignore-vuln PYSEC-2025-214
+          --ignore-vuln PYSEC-2025-215
+          --ignore-vuln PYSEC-2025-216
+          --ignore-vuln PYSEC-2025-217
+          --ignore-vuln PYSEC-2025-218
+          --ignore-vuln GHSA-f4j7-r4q5-qw2c' --
         language: system
         pass_filenames: false
         stages: [pre-push, manual]

docs/ar/changelog.mdx

@@ -4,6 +4,44 @@ description: "تحديثات المنتج والتحسينات وإصلاحات
 icon: "clock"
 mode: "wide"
 ---
+<Update label="28 مايو 2026">
+  ## v1.14.6
+
+  [عرض الإصدار على GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.6)
+
+  ## ما الذي تغير
+
+  ### الميزات
+  - تحسين StdioTransport لمنع تسرب متغيرات البيئة
+  - تعزيز تكوين التخطيط ومعالجة الملاحظات
+  - إعلان env_vars على DatabricksQueryTool
+  - إضافة وثائق خطة التحكم في الوكيل
+
+  ### إصلاحات الأخطاء
+  - إصلاح تسرب المخرجات المنظمة في حلقات استدعاء الأدوات
+  - حذف ردود الاستدعاء غير القابلة للعودة وحالة المحول في نقطة التحقق
+  - تسلسل الحقول من النوع [BaseModel] كـ JSON schema في نقطة التحقق
+  - تجنب مهمة orphan task_started عند استعادة نطاق الاستئناف
+  - السماح لـ AgentExecutor بالاستعادة من نقطة التحقق
+  - تصحيح خطأ الكتابة من mongodb إلى pymongo في package_dependencies
+
+  ### الوثائق
+  - إضافة كتلة تنقل وثائق ACP (بيتا) إلى صفحات خطة التحكم في الوكيل
+  - إزالة المراجع إلى العمليات التوافقية من صفحة العمليات
+  - إعادة هيكلة صفحة نقاط التحقق
+  - توثيق خطوة تثبيت حزمة الإدارة لمرة واحدة
+  - نقل Secrets Manager / Workload Identity من replicated-config
+  - إزالة تعبيرات `{" "}` JSX التي تكسر عرض `<Steps>`
+
+  ### إعادة الهيكلة
+  - نقل مستودع المهارات إلى experimental + CREWAI_EXPERIMENTAL gate
+
+  ## المساهمون
+
+  @akaKuruma, @alex-clawd, @github-actions[bot], @greysonlalonde, @heitorado, @iris-clawd, @lorenzejay, @lucasgomide, @mattatcha, @thiagomoretto, @vinibrsl
+
+</Update>
+
 <Update label="27 مايو 2026">
   ## v1.14.6a2
 

docs/ar/concepts/processes.mdx

@@ -16,7 +16,6 @@ mode: "wide"
 
 - **تسلسلي**: ينفذ المهام بالتتابع، مما يضمن إكمال المهام بتقدم منظم.
 - **هرمي**: ينظم المهام في تسلسل إداري هرمي، حيث يتم تفويض المهام وتنفيذها بناءً على سلسلة أوامر منظمة. يجب تحديد نموذج لغة المدير (`manager_llm`) أو وكيل مدير مخصص (`manager_agent`) في الطاقم لتفعيل العملية الهرمية، مما يسهّل إنشاء وإدارة المهام من قبل المدير.
-- **العملية التوافقية (مخطط لها)**: تهدف إلى اتخاذ القرارات بشكل تعاوني بين الوكلاء حول تنفيذ المهام، وتقدم هذه العملية نهجًا ديمقراطيًا لإدارة المهام داخل CrewAI. وهي مخطط لها للتطوير المستقبلي وغير مطبقة حاليًا في قاعدة الكود.
 
 ## دور العمليات في العمل الجماعي
 تُمكّن العمليات الوكلاء الأفراد من العمل كوحدة متماسكة، مما يبسّط جهودهم لتحقيق أهداف مشتركة بكفاءة وتناسق.
@@ -59,9 +58,9 @@ crew = Crew(
 
 ## فئة Process: نظرة عامة مفصلة
 
-تم تنفيذ فئة `Process` كتعداد (`Enum`)، مما يضمن أمان الأنواع ويقيّد قيم العملية على الأنواع المحددة (`sequential`، `hierarchical`). العملية التوافقية مخطط لإدراجها مستقبلاً، مما يؤكد التزامنا بالتطوير والابتكار المستمر.
+تم تنفيذ فئة `Process` كتعداد (`Enum`)، مما يضمن أمان الأنواع ويقيّد قيم العملية على الأنواع المحددة (`sequential`، `hierarchical`).
 
 ## الخلاصة
 
 التعاون المنظم الذي تسهّله العمليات داخل CrewAI ضروري لتمكين العمل الجماعي المنهجي بين الوكلاء.
-تم تحديث هذه الوثائق لتعكس أحدث الميزات والتحسينات والتكامل المخطط للعملية التوافقية، مما يضمن وصول المستخدمين إلى أحدث المعلومات وأكثرها شمولاً.
+تم تحديث هذه الوثائق لتعكس أحدث الميزات والتحسينات، مما يضمن وصول المستخدمين إلى أحدث المعلومات وأكثرها شمولاً.

docs/ar/enterprise/features/agent-control-plane/monitoring.mdx

@@ -6,6 +6,14 @@ icon: "gauge"
 mode: "wide"
 ---
 
+<Info>
+  **تنقل وثائق ACP (إصدار تجريبي)**
+
+  - [نظرة عامة](/ar/enterprise/features/agent-control-plane/overview)
+  - **المراقبة** *(أنت هنا)*
+  - [القواعد](/ar/enterprise/features/agent-control-plane/rules)
+</Info>
+
 ## نظرة عامة
 
 تبويب **Automations** هو عرض العمليات للقراءة فقط في [Agent Control Plane](/ar/enterprise/features/agent-control-plane/overview). يجمع بين بطاقتَي مقاييس و sankey تفاعلي وجدولين فرعيين — **Automations** و **Consumption** — يمكنك البحث والتصفية والفرز فيهما.

docs/ar/enterprise/features/agent-control-plane/overview.mdx

@@ -5,6 +5,14 @@ sidebarTitle: نظرة عامة
 icon: "book-open"
 ---
 
+<Info>
+  **تنقل وثائق ACP (إصدار تجريبي)**
+
+  - **نظرة عامة** *(أنت هنا)*
+  - [المراقبة](/ar/enterprise/features/agent-control-plane/monitoring)
+  - [القواعد](/ar/enterprise/features/agent-control-plane/rules)
+</Info>
+
 ## نظرة عامة
 
 **Agent Control Plane** (ACP) هو مركز العمليات لكل ما يعمل لديك على CrewAI AMP. إنها شاشة واحدة — مقسّمة إلى تبويبَي **Automations** و **Rules** — تمنح فريقك القدرة على:

docs/ar/enterprise/features/agent-control-plane/rules.mdx

@@ -6,6 +6,14 @@ icon: "shield-check"
 mode: "wide"
 ---
 
+<Info>
+  **تنقل وثائق ACP (إصدار تجريبي)**
+
+  - [نظرة عامة](/ar/enterprise/features/agent-control-plane/overview)
+  - [المراقبة](/ar/enterprise/features/agent-control-plane/monitoring)
+  - **القواعد** *(أنت هنا)*
+</Info>
+
 ## نظرة عامة
 
 تتيح لك القواعد تطبيق سياسات — اليوم: **PII Redaction** — عبر العديد من الأتمتات دفعة واحدة، بدلاً من ضبط كل deployment على حدة. افتح تبويب **Rules** في [Agent Control Plane](/ar/enterprise/features/agent-control-plane/overview) لإدارتها.

docs/ar/enterprise/integrations/snowflake.mdx

@@ -0,0 +1,134 @@
+---
+title: تكامل Snowflake
+description: "ربط وكلاء CrewAI بـ Snowflake Cortex Analyst و Cortex Search وتنفيذ SQL من خلال خادم MCP المُدار من Snowflake."
+icon: "snowflake"
+mode: "wide"
+---
+
+## نظرة عامة
+
+اربط وكلاء CrewAI مباشرة ببيانات Snowflake الخاصة بك من خلال [خادم MCP المُدار من Snowflake](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp). يتيح تكامل Snowflake لوكلائك الاستعلام عن البيانات المنظمة باستخدام **Cortex Analyst**، والبحث في البيانات غير المنظمة باستخدام **Cortex Search**، وتنفيذ SQL مُدار على مستودعات البيانات الخاصة بك — كل ذلك دون كتابة أو استضافة أي كود للموصّل.
+
+داخلياً، تكامل Snowflake هو غلاف مُدار حول دعم [Custom MCP Server](/ar/enterprise/guides/custom-mcp-server) في CrewAI. يكشف Snowflake عن قدرات Cortex AI الخاصة به من خلال نقطة نهاية [Model Context Protocol](https://modelcontextprotocol.io/)، ويتصل CrewAI بها بشكل آمن نيابةً عنك. أي أداة تكشفها على جانب Snowflake — Cortex Analyst أو Cortex Search أو تنفيذ SQL أو Cortex Agents أو أدواتك المخصصة — تصبح متاحة لطواقمك.
+
+## القدرات الرئيسية
+
+<CardGroup cols={3}>
+  <Card title="Cortex Analyst" icon="chart-bar">
+    اطرح أسئلة بلغة طبيعية ودع [Cortex Analyst](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst) يولّد وينفذ SQL على بياناتك **المنظمة** باستخدام نماذج دلالية غنية.
+  </Card>
+  <Card title="Cortex Search" icon="magnifying-glass">
+    استرجع البيانات **غير المنظمة** ذات الصلة لسير عمل RAG والمعرفة باستخدام [Cortex Search](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-search/cortex-search-overview)، خدمة البحث المُدارة بالكامل من Snowflake.
+  </Card>
+  <Card title="تنفيذ SQL" icon="database">
+    نفّذ استعلامات SQL مُدارة مباشرة على مستودعات Snowflake الخاصة بك، مع وضع القراءة فقط القابل للتكوين، والمهلات الزمنية، واختيار المستودع.
+  </Card>
+</CardGroup>
+
+نظراً لأن التكامل يكشف عن أي أدوات ينشرها خادم MCP الخاص بك، يمكنك أيضاً كشف **Cortex Agents** و**الأدوات المخصصة** (الدوال المعرّفة من المستخدم والإجراءات المخزّنة) لوكلاء CrewAI.
+
+## المتطلبات الأساسية
+
+قبل استخدام تكامل Snowflake، تأكد من توفر ما يلي:
+
+- حساب [CrewAI AMP](https://app.crewai.com) مع اشتراك فعّال
+- حساب Snowflake مع إمكانية الوصول إلى ميزات Cortex AI
+- [خادم MCP مُدار من Snowflake](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp) مُكوّن بالأدوات التي تريد كشفها
+- صلاحيات Snowflake المناسبة (USAGE/SELECT) على خادم MCP والكائنات الأساسية
+
+## إعداد خادم Snowflake MCP
+
+يعمل خادم MCP المُدار من Snowflake داخل حساب Snowflake الخاص بك ويحدد الأدوات المتاحة للعملاء الخارجيين مثل CrewAI. أنشئ واحداً باستخدام أمر [`CREATE MCP SERVER`](https://docs.snowflake.com/en/sql-reference/sql/create-mcp-server)، مع سرد خدمات Cortex Search وعروض Cortex Analyst الدلالية وأدوات SQL التي تريد كشفها.
+
+```sql
+CREATE MCP SERVER my_mcp_server
+  FROM SPECIFICATION $$
+    tools:
+      - name: "sales_analyst"
+        type: "CORTEX_ANALYST"
+        identifier: "MY_DATABASE.MY_SCHEMA.sales_semantic_view"
+        description: "Answer questions about sales metrics"
+      - name: "docs_search"
+        type: "CORTEX_SEARCH_SERVICE_QUERY"
+        identifier: "MY_DATABASE.MY_SCHEMA.support_docs_search"
+        description: "Search internal support documentation"
+      - name: "run_sql"
+        type: "SQL_EXECUTION"
+        description: "Execute read-only SQL queries"
+  $$;
+```
+
+<Note>
+تتبع نقطة نهاية MCP التنسيق `https://<account_URL>/api/v2/databases/{database}/schemas/{schema}/mcp-servers/{name}`. يبني CrewAI هذا العنوان تلقائياً من **عنوان URL للحساب** و**قاعدة البيانات** و**المخطط** و**اسم خادم MCP** الذي تقدمه عند تكوين التكامل.
+</Note>
+
+للمواصفات الكاملة — بما في ذلك Cortex Agents والأدوات المخصصة وحدود حجم الاستجابة وخيارات الحوكمة — راجع [وثائق خادم MCP المُدار من Snowflake](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp).
+
+## ربط Snowflake في CrewAI AMP
+
+<Frame>
+    <img src="/images/enterprise/snowflake-configure.png" alt="تكوين تكامل Snowflake في CrewAI AMP" />
+</Frame>
+
+<Steps>
+    <Step title="فتح الأدوات والتكاملات">
+        انتقل إلى **الأدوات والتكاملات** في الشريط الجانبي الأيسر لـ CrewAI AMP، وابحث عن **Snowflake** في قائمة التطبيقات، وافتح لوحة التكوين الخاصة به.
+    </Step>
+
+    <Step title="تقديم تفاصيل الاتصال">
+        املأ حقول الاتصال التي يستخدمها CrewAI للوصول إلى خادم Snowflake MCP الخاص بك:
+
+        | الحقل | مطلوب | الوصف |
+        |-------|-------|-------|
+        | **الاسم** | نعم | اسم وصفي لهذا الاتصال (القيمة الافتراضية `Snowflake`). |
+        | **الوصف** | لا | ملخص اختياري لما يوفره هذا الاتصال. |
+        | **عنوان URL للحساب** | نعم | عنوان URL لحساب Snowflake الخاص بك، مثل `xy12345.us-east-1.snowflakecomputing.com`. |
+        | **قاعدة البيانات** | نعم | قاعدة البيانات التي تحتوي على خادم MCP الخاص بك (مثل `MY_DATABASE`). |
+        | **المخطط** | نعم | المخطط الذي يحتوي على خادم MCP الخاص بك (مثل `MY_SCHEMA`). |
+        | **اسم خادم MCP** | نعم | اسم كائن خادم MCP الذي أنشأته في Snowflake (مثل `MY_MCP_SERVER`). |
+    </Step>
+
+    <Step title="اختيار طريقة المصادقة">
+        اختر كيفية مصادقة CrewAI مع Snowflake. يُوصى باستخدام **OAuth**.
+
+        - **استخدام OAuth** — اتصل بشكل آمن باستخدام OAuth 2.0 للمصادقة القائمة على الرموز دون مشاركة بيانات الاعتماد الخاصة بك. يتعامل CrewAI مع تدفق التفويض الكامل ويجدد الرموز تلقائياً. انسخ **عنوان URI لإعادة التوجيه** المعروض في النموذج (`https://oauth.crewai.com/oauth/add`) وسجّله كعنوان URI لإعادة التوجيه المعتمد في [تكامل أمان OAuth](https://docs.snowflake.com/en/user-guide/oauth-custom) في Snowflake.
+        - **استخدام رمز وصول شخصي** — المصادقة باستخدام [رمز وصول برمجي](https://docs.snowflake.com/en/user-guide/programmatic-access-tokens) مُنشأ من إعدادات حساب Snowflake الخاص بك. قم بتعيين دور بأقل صلاحيات للرمز للحد من التعرض.
+    </Step>
+
+    <Step title="المصادقة">
+        انقر على **المصادقة**. بالنسبة لـ OAuth، ستتم إعادة توجيهك إلى Snowflake لتفويض الوصول. بمجرد المصادقة، يظهر خادم Snowflake في قائمة الاتصالات وتصبح أدواته متاحة لطواقمك.
+    </Step>
+</Steps>
+
+<Tip>
+مع OAuth، يتم مصادقة كل مستخدم بشكل فردي وتُنفّذ الاستعلامات بدور `DEFAULT_ROLE` الخاص به في Snowflake. تأكد من أن المستخدمين المتصلين لديهم دور ومستودع افتراضي محدد (`ALTER USER <username> SET DEFAULT_ROLE = '<role>' DEFAULT_WAREHOUSE = '<warehouse>'`) حتى تتوفر موارد الحوسبة لأدوات Cortex Analyst و SQL.
+</Tip>
+
+## استخدام أدوات Snowflake في طواقمك
+
+بمجرد الاتصال، تظهر الأدوات التي يكشفها خادم MCP الخاص بك إلى جانب الاتصالات المدمجة في صفحة **الأدوات والتكاملات**. يمكنك:
+
+- **تعيين الأدوات للوكلاء** في طواقمك تماماً مثل أي أداة CrewAI أخرى.
+- **إدارة الرؤية** للتحكم في أعضاء الفريق الذين يمكنهم استخدام الاتصال.
+- **تعديل أو إزالة** الاتصال في أي وقت من قائمة الاتصالات.
+
+يمكن لوكلائك الآن سؤال Cortex Analyst عن المقاييس، وتشغيل Cortex Search على مستنداتك، وتنفيذ SQL — مع تدفق النتائج تلقائياً إلى استدلالهم.
+
+<Warning>
+يفرض Snowflake الحوكمة على خادم MCP: يحدد التحكم في الوصول القائم على الأدوار الأدوات التي يمكن للمستخدم اكتشافها واستدعاؤها، وتنطبق حدود على حجم الاستجابة وعدد الأدوات (بحد أقصى 50 لكل خادم) وعمق التكرار. إذا فشل استدعاء أداة، تأكد من أن دور المستخدم المتصل لديه الصلاحيات المطلوبة على خادم MCP والكائنات الأساسية.
+</Warning>
+
+## معرفة المزيد
+
+<CardGroup cols={2}>
+  <Card title="خادم MCP المُدار من Snowflake" icon="snowflake" href="https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp">
+    الوثائق الرسمية من Snowflake لإنشاء وإدارة خادم MCP.
+  </Card>
+  <Card title="خوادم Custom MCP في CrewAI" icon="plug" href="/ar/enterprise/guides/custom-mcp-server">
+    تعرّف على كيفية اتصال CrewAI بأي خادم MCP، الأساس الذي يبني عليه تكامل Snowflake.
+  </Card>
+</CardGroup>
+
+<Card title="تحتاج مساعدة؟" icon="headset" href="mailto:support@crewai.com">
+  تواصل مع فريق الدعم للحصول على المساعدة في تكامل Snowflake أو استكشاف الأخطاء وإصلاحها.
+</Card>

docs/en/changelog.mdx

@@ -4,6 +4,44 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="May 28, 2026">
+  ## v1.14.6
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.6)
+
+  ## What's Changed
+
+  ### Features
+  - Enhance StdioTransport to prevent environment variable leakage
+  - Enhance planning configuration and observation handling
+  - Declare env_vars on DatabricksQueryTool
+  - Add Agent Control Plane docs
+
+  ### Bug Fixes
+  - Fix structured output leaks in tool-calling loops
+  - Drop unroundtrippable callbacks and adapter state in checkpoint
+  - Serialize type[BaseModel] fields as JSON schema in checkpoint
+  - Avoid orphan task_started on resume scope restore
+  - Allow AgentExecutor to restore from checkpoint
+  - Correct mongodb typo to pymongo in package_dependencies
+
+  ### Documentation
+  - Add ACP (Beta) docs navigation block to Agent Control Plane pages
+  - Remove consensual process references from processes page
+  - Restructure checkpointing page
+  - Document one-time admin package install step
+  - Migrate Secrets Manager / Workload Identity from replicated-config
+  - Remove `{" "}` JSX expressions breaking `<Steps>` render
+
+  ### Refactoring
+  - Move Skills Repository to experimental + CREWAI_EXPERIMENTAL gate
+
+  ## Contributors
+
+  @akaKuruma, @alex-clawd, @github-actions[bot], @greysonlalonde, @heitorado, @iris-clawd, @lorenzejay, @lucasgomide, @mattatcha, @thiagomoretto, @vinibrsl
+
+</Update>
+
 <Update label="May 27, 2026">
   ## v1.14.6a2
 

docs/en/concepts/processes.mdx

@@ -16,7 +16,6 @@ mode: "wide"
 
 - **Sequential**: Executes tasks sequentially, ensuring tasks are completed in an orderly progression.
 - **Hierarchical**: Organizes tasks in a managerial hierarchy, where tasks are delegated and executed based on a structured chain of command. A manager language model (`manager_llm`) or a custom manager agent (`manager_agent`) must be specified in the crew to enable the hierarchical process, facilitating the creation and management of tasks by the manager.
-- **Consensual Process (Planned)**: Aiming for collaborative decision-making among agents on task execution, this process type introduces a democratic approach to task management within CrewAI. It is planned for future development and is not currently implemented in the codebase.
 
 ## The Role of Processes in Teamwork
 Processes enable individual agents to operate as a cohesive unit, streamlining their efforts to achieve common objectives with efficiency and coherence.
@@ -59,9 +58,9 @@ Emulates a corporate hierarchy, CrewAI allows specifying a custom manager agent
 
 ## Process Class: Detailed Overview
 
-The `Process` class is implemented as an enumeration (`Enum`), ensuring type safety and restricting process values to the defined types (`sequential`, `hierarchical`). The consensual process is planned for future inclusion, emphasizing our commitment to continuous development and innovation.
+The `Process` class is implemented as an enumeration (`Enum`), ensuring type safety and restricting process values to the defined types (`sequential`, `hierarchical`).
 
 ## Conclusion
 
 The structured collaboration facilitated by processes within CrewAI is crucial for enabling systematic teamwork among agents. 
-This documentation has been updated to reflect the latest features, enhancements, and the planned integration of the Consensual Process, ensuring users have access to the most current and comprehensive information.
+This documentation has been updated to reflect the latest features and enhancements, ensuring users have access to the most current and comprehensive information.

docs/en/enterprise/features/agent-control-plane/monitoring.mdx

@@ -6,6 +6,14 @@ icon: "gauge"
 mode: "wide"
 ---
 
+<Info>
+  **ACP (Beta) Docs Navigation**
+
+  - [Overview](/en/enterprise/features/agent-control-plane/overview)
+  - **Monitoring** *(you are here)*
+  - [Rules](/en/enterprise/features/agent-control-plane/rules)
+</Info>
+
 ## Overview
 
 The **Automations** tab is the read-only operations view of the [Agent Control Plane](/en/enterprise/features/agent-control-plane/overview). It combines two metric cards, an interactive sankey, and two sub-tables — **Automations** and **Consumption** — that you can search, filter, and sort.

docs/en/enterprise/features/agent-control-plane/overview.mdx

@@ -5,6 +5,14 @@ sidebarTitle: Overview
 icon: "book-open"
 ---
 
+<Info>
+  **ACP (Beta) Docs Navigation**
+
+  - **Overview** *(you are here)*
+  - [Monitoring](/en/enterprise/features/agent-control-plane/monitoring)
+  - [Rules](/en/enterprise/features/agent-control-plane/rules)
+</Info>
+
 ## Overview
 
 The **Agent Control Plane** (ACP) is the operations hub for everything you have running on CrewAI AMP. It is a single screen — split into **Automations** and **Rules** tabs — that lets your team:

docs/en/enterprise/features/agent-control-plane/rules.mdx

@@ -6,6 +6,14 @@ icon: "shield-check"
 mode: "wide"
 ---
 
+<Info>
+  **ACP (Beta) Docs Navigation**
+
+  - [Overview](/en/enterprise/features/agent-control-plane/overview)
+  - [Monitoring](/en/enterprise/features/agent-control-plane/monitoring)
+  - **Rules** *(you are here)*
+</Info>
+
 ## Overview
 
 Rules let you apply policies — today: **PII Redaction** — across many automations at once, instead of configuring each deployment individually. Open the **Rules** tab in the [Agent Control Plane](/en/enterprise/features/agent-control-plane/overview) to manage them.

docs/en/enterprise/integrations/snowflake.mdx

@@ -0,0 +1,134 @@
+---
+title: Snowflake Integration
+description: "Connect CrewAI agents to Snowflake Cortex Analyst, Cortex Search, and SQL execution through the Snowflake-managed MCP server."
+icon: "snowflake"
+mode: "wide"
+---
+
+## Overview
+
+Connect your CrewAI agents directly to your Snowflake data through the [Snowflake-managed MCP server](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp). The Snowflake integration lets your agents query structured data with **Cortex Analyst**, search unstructured data with **Cortex Search**, and run governed SQL against your warehouses — all without writing or hosting any connector code.
+
+Under the hood, the Snowflake integration is a managed wrapper around CrewAI's [Custom MCP Server](/en/enterprise/guides/custom-mcp-server) support. Snowflake exposes its Cortex AI capabilities through a [Model Context Protocol](https://modelcontextprotocol.io/) endpoint, and CrewAI connects to it securely on your behalf. Any tool you expose on the Snowflake side — Cortex Analyst, Cortex Search, SQL execution, Cortex Agents, or your own custom tools — becomes available to your crews.
+
+## Key Capabilities
+
+<CardGroup cols={3}>
+  <Card title="Cortex Analyst" icon="chart-bar">
+    Ask questions in natural language and let [Cortex Analyst](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst) generate and run SQL against your **structured** data using rich semantic models.
+  </Card>
+  <Card title="Cortex Search" icon="magnifying-glass">
+    Retrieve relevant **unstructured** data for RAG and knowledge workflows with [Cortex Search](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-search/cortex-search-overview), Snowflake's fully managed search service.
+  </Card>
+  <Card title="SQL Execution" icon="database">
+    Run governed SQL queries directly against your Snowflake warehouses, with configurable read-only mode, timeouts, and warehouse selection.
+  </Card>
+</CardGroup>
+
+Because the integration surfaces whatever tools your MCP server publishes, you can also expose **Cortex Agents** and **custom tools** (user-defined functions and stored procedures) to your CrewAI agents.
+
+## Prerequisites
+
+Before using the Snowflake integration, ensure you have:
+
+- A [CrewAI AMP](https://app.crewai.com) account with an active subscription
+- A Snowflake account with access to Cortex AI features
+- A [Snowflake-managed MCP server](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp) configured with the tools you want to expose
+- Appropriate Snowflake privileges (USAGE/SELECT) on the MCP server and its underlying objects
+
+## Setting Up the Snowflake MCP Server
+
+The Snowflake-managed MCP server runs inside your Snowflake account and defines which tools are available to external clients like CrewAI. Create one with the [`CREATE MCP SERVER`](https://docs.snowflake.com/en/sql-reference/sql/create-mcp-server) command, listing the Cortex Search services, Cortex Analyst semantic views, and SQL tools you want to expose.
+
+```sql
+CREATE MCP SERVER my_mcp_server
+  FROM SPECIFICATION $$
+    tools:
+      - name: "sales_analyst"
+        type: "CORTEX_ANALYST"
+        identifier: "MY_DATABASE.MY_SCHEMA.sales_semantic_view"
+        description: "Answer questions about sales metrics"
+      - name: "docs_search"
+        type: "CORTEX_SEARCH_SERVICE_QUERY"
+        identifier: "MY_DATABASE.MY_SCHEMA.support_docs_search"
+        description: "Search internal support documentation"
+      - name: "run_sql"
+        type: "SQL_EXECUTION"
+        description: "Execute read-only SQL queries"
+  $$;
+```
+
+<Note>
+The MCP endpoint follows the format `https://<account_URL>/api/v2/databases/{database}/schemas/{schema}/mcp-servers/{name}`. CrewAI builds this URL automatically from the **Account URL**, **Database**, **Schema**, and **MCP Server Name** you provide when configuring the integration.
+</Note>
+
+For the complete specification — including Cortex Agents, custom tools, response-size limits, and governance options — see the [Snowflake-managed MCP server documentation](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp).
+
+## Connecting Snowflake in CrewAI AMP
+
+<Frame>
+    <img src="/images/enterprise/snowflake-configure.png" alt="Configure Snowflake integration in CrewAI AMP" />
+</Frame>
+
+<Steps>
+    <Step title="Open Tools & Integrations">
+        Navigate to **Tools & Integrations** in the left sidebar of CrewAI AMP, find **Snowflake** in the list of applications, and open its configuration panel.
+    </Step>
+
+    <Step title="Provide connection details">
+        Fill in the connection fields that CrewAI uses to reach your Snowflake MCP server:
+
+        | Field | Required | Description |
+        |-------|----------|-------------|
+        | **Name** | Yes | A descriptive name for this connection (defaults to `Snowflake`). |
+        | **Description** | No | An optional summary of what this connection provides. |
+        | **Account URL** | Yes | Your Snowflake account URL, e.g. `xy12345.us-east-1.snowflakecomputing.com`. |
+        | **Database** | Yes | The database that contains your MCP server (e.g. `MY_DATABASE`). |
+        | **Schema** | Yes | The schema that contains your MCP server (e.g. `MY_SCHEMA`). |
+        | **MCP Server Name** | Yes | The name of the MCP server object you created in Snowflake (e.g. `MY_MCP_SERVER`). |
+    </Step>
+
+    <Step title="Choose an authentication method">
+        Select how CrewAI authenticates to Snowflake. **OAuth** is recommended.
+
+        - **Use OAuth** — Connect securely using OAuth 2.0 for token-based authentication without sharing your credentials. CrewAI handles the full authorization flow and refreshes tokens automatically. Copy the **Redirect URI** shown in the form (`https://oauth.crewai.com/oauth/add`) and register it as an authorized redirect URI in your Snowflake [OAuth security integration](https://docs.snowflake.com/en/user-guide/oauth-custom).
+        - **Use personal access token** — Authenticate using a [programmatic access token](https://docs.snowflake.com/en/user-guide/programmatic-access-tokens) generated from your Snowflake account settings. Assign a least-privileged role to the token to limit exposure.
+    </Step>
+
+    <Step title="Authenticate">
+        Click **Authenticate**. For OAuth, you'll be redirected to Snowflake to authorize access. Once authenticated, the Snowflake server appears in your Connections and its tools become available to your crews.
+    </Step>
+</Steps>
+
+<Tip>
+With OAuth, each user authenticates individually and queries run with their Snowflake `DEFAULT_ROLE`. Make sure connecting users have a default role and warehouse set (`ALTER USER <username> SET DEFAULT_ROLE = '<role>' DEFAULT_WAREHOUSE = '<warehouse>'`) so Cortex Analyst and SQL tools have compute to run on.
+</Tip>
+
+## Using Snowflake Tools in Your Crews
+
+Once connected, the tools your MCP server exposes appear alongside built-in connections on the **Tools & Integrations** page. You can:
+
+- **Assign tools to agents** in your crews just like any other CrewAI tool.
+- **Manage visibility** to control which team members can use the connection.
+- **Edit or remove** the connection at any time from the Connections list.
+
+Your agents can now ask Cortex Analyst for metrics, run Cortex Search over your documents, and execute SQL — with results flowing back into their reasoning automatically.
+
+<Warning>
+Snowflake enforces governance on the MCP server: role-based access control determines which tools a user can discover and invoke, and limits apply to response size, tool count (max 50 per server), and recursion depth. If a tool call fails, confirm the connecting user's role has the required privileges on the MCP server and its underlying objects.
+</Warning>
+
+## Learn More
+
+<CardGroup cols={2}>
+  <Card title="Snowflake-managed MCP Server" icon="snowflake" href="https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp">
+    Official Snowflake documentation for creating and governing the MCP server.
+  </Card>
+  <Card title="Custom MCP Servers in CrewAI" icon="plug" href="/en/enterprise/guides/custom-mcp-server">
+    Learn how CrewAI connects to any MCP server, the foundation the Snowflake integration builds on.
+  </Card>
+</CardGroup>
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with the Snowflake integration or troubleshooting.
+</Card>

docs/ko/changelog.mdx

@@ -4,6 +4,44 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="2026년 5월 28일">
+  ## v1.14.6
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.14.6)
+
+  ## 변경 사항
+
+  ### 기능
+  - 환경 변수 유출을 방지하기 위해 StdioTransport 강화
+  - 계획 구성 및 관찰 처리 개선
+  - DatabricksQueryTool에서 env_vars 선언
+  - 에이전트 제어 평면 문서 추가
+
+  ### 버그 수정
+  - 도구 호출 루프에서 구조화된 출력 유출 수정
+  - 체크포인트에서 원형으로 돌아갈 수 없는 콜백 및 어댑터 상태 제거
+  - 체크포인트에서 type[BaseModel] 필드를 JSON 스키마로 직렬화
+  - 복원 범위 복원 시 고아 task_started 방지
+  - AgentExecutor가 체크포인트에서 복원할 수 있도록 허용
+  - package_dependencies에서 mongodb 오타를 pymongo로 수정
+
+  ### 문서
+  - 에이전트 제어 평면 페이지에 ACP (Beta) 문서 탐색 블록 추가
+  - 프로세스 페이지에서 합의 프로세스 참조 제거
+  - 체크포인트 페이지 구조 재편성
+  - 일회성 관리자 패키지 설치 단계 문서화
+  - Secrets Manager / Workload Identity를 replicated-config에서 마이그레이션
+  - `<Steps>` 렌더링을 방해하는 `{" "}` JSX 표현 제거
+
+  ### 리팩토링
+  - Skills Repository를 실험적 + CREWAI_EXPERIMENTAL 게이트로 이동
+
+  ## 기여자
+
+  @akaKuruma, @alex-clawd, @github-actions[bot], @greysonlalonde, @heitorado, @iris-clawd, @lorenzejay, @lucasgomide, @mattatcha, @thiagomoretto, @vinibrsl
+
+</Update>
+
 <Update label="2026년 5월 27일">
   ## v1.14.6a2
 

docs/ko/concepts/processes.mdx

@@ -16,7 +16,6 @@ mode: "wide"
 
 - **순차적(Sequential)**: 작업을 순차적으로 실행하여 작업이 질서 있게 진행되도록 보장합니다.
 - **계층적(Hierarchical)**: 작업을 관리 계층 구조로 조직하며, 작업은 체계적인 명령 체계를 기반으로 위임 및 실행됩니다. 계층적 프로세스를 활성화하려면 매니저 언어 모델(`manager_llm`) 또는 커스텀 매니저 에이전트(`manager_agent`)를 crew에서 지정해야 하며, 이를 통해 매니저가 작업을 생성하고 관리할 수 있도록 지원합니다.
-- **합의 프로세스(Consensual Process, 계획됨)**: 에이전트들 간에 작업 실행에 대한 협력적 의사결정을 목표로 하며, 이 프로세스 유형은 CrewAI 내에서 작업 관리를 민주적으로 접근하도록 도입됩니다. 앞으로 개발될 예정이며, 현재 코드베이스에는 구현되어 있지 않습니다.
 
 ## 팀워크에서 프로세스의 역할
 프로세스는 개별 에이전트가 통합된 단위로 작동할 수 있도록 하여, 공통된 목표를 효율적이고 일관성 있게 달성하도록 노력하는 과정을 간소화합니다.
@@ -59,9 +58,9 @@ crew = Crew(
 
 ## Process 클래스: 상세 개요
 
-`Process` 클래스는 열거형(`Enum`)으로 구현되어 타입 안전성을 보장하며, 프로세스 값을 정의된 타입(`sequential`, `hierarchical`)으로 제한합니다. 합의 기반(consensual) 프로세스는 향후 추가될 예정이며, 이는 지속적인 개발과 혁신에 대한 우리의 의지를 강조합니다.
+`Process` 클래스는 열거형(`Enum`)으로 구현되어 타입 안전성을 보장하며, 프로세스 값을 정의된 타입(`sequential`, `hierarchical`)으로 제한합니다.
 
 ## 결론
 
 CrewAI 내의 프로세스를 통해 촉진되는 구조화된 협업은 에이전트 간 체계적인 팀워크를 가능하게 하는 데 매우 중요합니다.  
-이 문서는 최신 기능, 향상 사항, 그리고 예정된 Consensual Process 통합을 반영하도록 업데이트되었으며, 사용자가 가장 최신이고 포괄적인 정보를 이용할 수 있도록 보장합니다.
+이 문서는 최신 기능과 향상 사항을 반영하도록 업데이트되었으며, 사용자가 가장 최신이고 포괄적인 정보를 이용할 수 있도록 보장합니다.

docs/ko/enterprise/features/agent-control-plane/monitoring.mdx

@@ -6,6 +6,14 @@ icon: "gauge"
 mode: "wide"
 ---
 
+<Info>
+  **ACP (베타) 문서 내비게이션**
+
+  - [개요](/ko/enterprise/features/agent-control-plane/overview)
+  - **모니터링** *(현재 페이지)*
+  - [규칙](/ko/enterprise/features/agent-control-plane/rules)
+</Info>
+
 ## 개요
 
 **Automations** 탭은 [Agent Control Plane](/ko/enterprise/features/agent-control-plane/overview)의 읽기 전용 운영 뷰입니다. 두 개의 메트릭 카드, 인터랙티브 sankey, 그리고 **Automations**와 **Consumption** 두 개의 서브 테이블을 결합해 검색·필터·정렬을 지원합니다.

docs/ko/enterprise/features/agent-control-plane/overview.mdx

@@ -5,6 +5,14 @@ sidebarTitle: 개요
 icon: "book-open"
 ---
 
+<Info>
+  **ACP (베타) 문서 내비게이션**
+
+  - **개요** *(현재 페이지)*
+  - [모니터링](/ko/enterprise/features/agent-control-plane/monitoring)
+  - [규칙](/ko/enterprise/features/agent-control-plane/rules)
+</Info>
+
 ## 개요
 
 **Agent Control Plane**(ACP)은 CrewAI AMP에서 실행 중인 모든 워크로드를 위한 운영 허브입니다. **Automations**와 **Rules** 두 개의 탭으로 구성된 단일 화면에서 다음 작업을 할 수 있습니다:

docs/ko/enterprise/features/agent-control-plane/rules.mdx

@@ -6,6 +6,14 @@ icon: "shield-check"
 mode: "wide"
 ---
 
+<Info>
+  **ACP (베타) 문서 내비게이션**
+
+  - [개요](/ko/enterprise/features/agent-control-plane/overview)
+  - [모니터링](/ko/enterprise/features/agent-control-plane/monitoring)
+  - **규칙** *(현재 페이지)*
+</Info>
+
 ## 개요
 
 규칙(Rules)은 각 deployment를 개별 설정하는 대신, 정책 — 현재: **PII Redaction** — 을 한 번에 여러 자동화에 적용할 수 있게 해줍니다. 관리하려면 [Agent Control Plane](/ko/enterprise/features/agent-control-plane/overview)에서 **Rules** 탭을 엽니다.

docs/ko/enterprise/integrations/snowflake.mdx

@@ -0,0 +1,134 @@
+---
+title: Snowflake 연동
+description: "Snowflake 관리형 MCP 서버를 통해 CrewAI 에이전트를 Snowflake Cortex Analyst, Cortex Search 및 SQL 실행에 연결합니다."
+icon: "snowflake"
+mode: "wide"
+---
+
+## 개요
+
+[Snowflake 관리형 MCP 서버](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp)를 통해 CrewAI 에이전트를 Snowflake 데이터에 직접 연결하세요. Snowflake 연동을 사용하면 에이전트가 **Cortex Analyst**로 구조화된 데이터를 쿼리하고, **Cortex Search**로 비구조화된 데이터를 검색하며, 커넥터 코드를 작성하거나 호스팅할 필요 없이 웨어하우스에 대해 관리되는 SQL을 실행할 수 있습니다.
+
+내부적으로 Snowflake 연동은 CrewAI의 [Custom MCP Server](/ko/enterprise/guides/custom-mcp-server) 지원을 기반으로 하는 관리형 래퍼입니다. Snowflake는 [Model Context Protocol](https://modelcontextprotocol.io/) 엔드포인트를 통해 Cortex AI 기능을 노출하며, CrewAI가 이를 안전하게 연결합니다. Snowflake 측에서 노출하는 모든 도구 — Cortex Analyst, Cortex Search, SQL 실행, Cortex Agents 또는 사용자 정의 도구 — 가 크루에서 사용할 수 있게 됩니다.
+
+## 주요 기능
+
+<CardGroup cols={3}>
+  <Card title="Cortex Analyst" icon="chart-bar">
+    자연어로 질문하고 [Cortex Analyst](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst)가 풍부한 시맨틱 모델을 사용하여 **구조화된** 데이터에 대해 SQL을 생성하고 실행하도록 합니다.
+  </Card>
+  <Card title="Cortex Search" icon="magnifying-glass">
+    Snowflake의 완전 관리형 검색 서비스인 [Cortex Search](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-search/cortex-search-overview)를 사용하여 RAG 및 지식 워크플로우를 위한 관련 **비구조화된** 데이터를 검색합니다.
+  </Card>
+  <Card title="SQL 실행" icon="database">
+    구성 가능한 읽기 전용 모드, 타임아웃 및 웨어하우스 선택을 통해 Snowflake 웨어하우스에 대해 관리되는 SQL 쿼리를 직접 실행합니다.
+  </Card>
+</CardGroup>
+
+연동이 MCP 서버가 게시하는 도구를 노출하므로, **Cortex Agents** 및 **사용자 정의 도구**(사용자 정의 함수 및 저장 프로시저)도 CrewAI 에이전트에 노출할 수 있습니다.
+
+## 사전 준비 사항
+
+Snowflake 연동을 사용하기 전에 다음을 확인하십시오:
+
+- 활성 구독이 있는 [CrewAI AMP](https://app.crewai.com) 계정
+- Cortex AI 기능에 액세스할 수 있는 Snowflake 계정
+- 노출하려는 도구가 구성된 [Snowflake 관리형 MCP 서버](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp)
+- MCP 서버 및 기본 객체에 대한 적절한 Snowflake 권한(USAGE/SELECT)
+
+## Snowflake MCP 서버 설정
+
+Snowflake 관리형 MCP 서버는 Snowflake 계정 내에서 실행되며 CrewAI와 같은 외부 클라이언트에서 사용할 수 있는 도구를 정의합니다. [`CREATE MCP SERVER`](https://docs.snowflake.com/en/sql-reference/sql/create-mcp-server) 명령을 사용하여 노출하려는 Cortex Search 서비스, Cortex Analyst 시맨틱 뷰 및 SQL 도구를 나열하여 생성합니다.
+
+```sql
+CREATE MCP SERVER my_mcp_server
+  FROM SPECIFICATION $$
+    tools:
+      - name: "sales_analyst"
+        type: "CORTEX_ANALYST"
+        identifier: "MY_DATABASE.MY_SCHEMA.sales_semantic_view"
+        description: "Answer questions about sales metrics"
+      - name: "docs_search"
+        type: "CORTEX_SEARCH_SERVICE_QUERY"
+        identifier: "MY_DATABASE.MY_SCHEMA.support_docs_search"
+        description: "Search internal support documentation"
+      - name: "run_sql"
+        type: "SQL_EXECUTION"
+        description: "Execute read-only SQL queries"
+  $$;
+```
+
+<Note>
+MCP 엔드포인트는 `https://<account_URL>/api/v2/databases/{database}/schemas/{schema}/mcp-servers/{name}` 형식을 따릅니다. CrewAI는 연동 구성 시 제공하는 **계정 URL**, **데이터베이스**, **스키마** 및 **MCP 서버 이름**을 사용하여 이 URL을 자동으로 구성합니다.
+</Note>
+
+Cortex Agents, 사용자 정의 도구, 응답 크기 제한 및 거버넌스 옵션을 포함한 전체 사양은 [Snowflake 관리형 MCP 서버 문서](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp)를 참조하세요.
+
+## CrewAI AMP에서 Snowflake 연결
+
+<Frame>
+    <img src="/images/enterprise/snowflake-configure.png" alt="CrewAI AMP에서 Snowflake 연동 구성" />
+</Frame>
+
+<Steps>
+    <Step title="도구 및 연동 열기">
+        CrewAI AMP 왼쪽 사이드바에서 **도구 및 연동**으로 이동하고, 애플리케이션 목록에서 **Snowflake**를 찾아 구성 패널을 엽니다.
+    </Step>
+
+    <Step title="연결 세부 정보 제공">
+        CrewAI가 Snowflake MCP 서버에 연결하는 데 사용하는 연결 필드를 채웁니다:
+
+        | 필드 | 필수 | 설명 |
+        |------|------|------|
+        | **이름** | 예 | 이 연결의 설명적 이름(기본값: `Snowflake`). |
+        | **설명** | 아니오 | 이 연결이 제공하는 내용에 대한 선택적 요약. |
+        | **계정 URL** | 예 | Snowflake 계정 URL, 예: `xy12345.us-east-1.snowflakecomputing.com`. |
+        | **데이터베이스** | 예 | MCP 서버가 포함된 데이터베이스(예: `MY_DATABASE`). |
+        | **스키마** | 예 | MCP 서버가 포함된 스키마(예: `MY_SCHEMA`). |
+        | **MCP 서버 이름** | 예 | Snowflake에서 생성한 MCP 서버 객체의 이름(예: `MY_MCP_SERVER`). |
+    </Step>
+
+    <Step title="인증 방법 선택">
+        CrewAI가 Snowflake에 인증하는 방법을 선택합니다. **OAuth**가 권장됩니다.
+
+        - **OAuth 사용** — 자격 증명을 공유하지 않고 토큰 기반 인증을 위해 OAuth 2.0을 사용하여 안전하게 연결합니다. CrewAI가 전체 인증 흐름을 처리하고 자동으로 토큰을 갱신합니다. 양식에 표시된 **리디렉트 URI**(`https://oauth.crewai.com/oauth/add`)를 복사하여 Snowflake [OAuth 보안 연동](https://docs.snowflake.com/en/user-guide/oauth-custom)에 인증된 리디렉트 URI로 등록하세요.
+        - **개인 액세스 토큰 사용** — Snowflake 계정 설정에서 생성한 [프로그래밍 방식 액세스 토큰](https://docs.snowflake.com/en/user-guide/programmatic-access-tokens)을 사용하여 인증합니다. 노출을 제한하기 위해 토큰에 최소 권한 역할을 할당하세요.
+    </Step>
+
+    <Step title="인증">
+        **인증**을 클릭합니다. OAuth의 경우 Snowflake로 리디렉션되어 액세스를 승인합니다. 인증되면 Snowflake 서버가 연결 목록에 나타나고 해당 도구를 크루에서 사용할 수 있게 됩니다.
+    </Step>
+</Steps>
+
+<Tip>
+OAuth를 사용하면 각 사용자가 개별적으로 인증하며 쿼리는 해당 Snowflake `DEFAULT_ROLE`로 실행됩니다. 연결하는 사용자에게 기본 역할과 웨어하우스가 설정되어 있는지 확인하세요(`ALTER USER <username> SET DEFAULT_ROLE = '<role>' DEFAULT_WAREHOUSE = '<warehouse>'`). 그래야 Cortex Analyst 및 SQL 도구에 실행할 컴퓨팅이 있습니다.
+</Tip>
+
+## 크루에서 Snowflake 도구 사용
+
+연결되면 MCP 서버가 노출하는 도구가 **도구 및 연동** 페이지에서 기본 연결과 함께 표시됩니다. 다음을 수행할 수 있습니다:
+
+- 다른 CrewAI 도구처럼 크루의 **에이전트에 도구를 할당**합니다.
+- **가시성을 관리**하여 어떤 팀원이 연결을 사용할 수 있는지 제어합니다.
+- 연결 목록에서 언제든지 연결을 **편집하거나 제거**합니다.
+
+이제 에이전트가 Cortex Analyst에 메트릭을 요청하고, 문서에 대해 Cortex Search를 실행하고, SQL을 실행할 수 있으며 — 결과가 자동으로 추론에 반영됩니다.
+
+<Warning>
+Snowflake는 MCP 서버에 거버넌스를 적용합니다: 역할 기반 액세스 제어가 사용자가 발견하고 호출할 수 있는 도구를 결정하며, 응답 크기, 도구 수(서버당 최대 50개) 및 재귀 깊이에 제한이 적용됩니다. 도구 호출이 실패하면 연결하는 사용자의 역할에 MCP 서버 및 기본 객체에 대한 필수 권한이 있는지 확인하세요.
+</Warning>
+
+## 자세히 알아보기
+
+<CardGroup cols={2}>
+  <Card title="Snowflake 관리형 MCP 서버" icon="snowflake" href="https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp">
+    MCP 서버를 생성하고 관리하기 위한 공식 Snowflake 문서.
+  </Card>
+  <Card title="CrewAI의 Custom MCP 서버" icon="plug" href="/ko/enterprise/guides/custom-mcp-server">
+    CrewAI가 모든 MCP 서버에 연결하는 방법을 알아보세요. Snowflake 연동이 기반으로 하는 기초입니다.
+  </Card>
+</CardGroup>
+
+<Card title="도움이 필요하신가요?" icon="headset" href="mailto:support@crewai.com">
+  Snowflake 연동 또는 문제 해결에 대해 지원팀에 문의하세요.
+</Card>

docs/pt-BR/changelog.mdx

@@ -4,6 +4,44 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="28 mai 2026">
+  ## v1.14.6
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.14.6)
+
+  ## O que Mudou
+
+  ### Recursos
+  - Aprimorar StdioTransport para evitar vazamento de variáveis de ambiente
+  - Aprimorar a configuração de planejamento e o manuseio de observações
+  - Declarar env_vars no DatabricksQueryTool
+  - Adicionar documentação do Agente Control Plane
+
+  ### Correções de Bugs
+  - Corrigir vazamentos de saída estruturada em loops de chamada de ferramenta
+  - Remover callbacks e estado de adaptador que não podem ser retornados em checkpoint
+  - Serializar campos type[BaseModel] como esquema JSON em checkpoint
+  - Evitar tarefa órfã task_started na restauração de escopo de retomar
+  - Permitir que AgentExecutor restaure a partir de checkpoint
+  - Corrigir erro de digitação de mongodb para pymongo em package_dependencies
+
+  ### Documentação
+  - Adicionar bloco de navegação de documentação ACP (Beta) às páginas do Agente Control Plane
+  - Remover referências a processos consensuais da página de processos
+  - Reestruturar a página de checkpointing
+  - Documentar passo de instalação do pacote administrativo único
+  - Migrar Secrets Manager / Workload Identity de replicated-config
+  - Remover expressões JSX `{" "}` que quebram a renderização de `<Steps>`
+
+  ### Refatoração
+  - Mover Skills Repository para experimental + CREWAI_EXPERIMENTAL gate
+
+  ## Contribuidores
+
+  @akaKuruma, @alex-clawd, @github-actions[bot], @greysonlalonde, @heitorado, @iris-clawd, @lorenzejay, @lucasgomide, @mattatcha, @thiagomoretto, @vinibrsl
+
+</Update>
+
 <Update label="27 mai 2026">
   ## v1.14.6a2
 

docs/pt-BR/concepts/processes.mdx

@@ -16,7 +16,6 @@ mode: "wide"
 
 - **Sequencial**: Executa tarefas de forma sequencial, garantindo que as tarefas sejam concluídas em uma progressão ordenada.
 - **Hierárquico**: Organiza tarefas em uma hierarquia gerencial, onde as tarefas são delegadas e executadas com base numa cadeia de comando estruturada. Um modelo de linguagem de gerente (`manager_llm`) ou um agente gerente personalizado (`manager_agent`) deve ser especificado na crew para habilitar o processo hierárquico, facilitando a criação e o gerenciamento de tarefas pelo gerente.
-- **Processo Consensual (Planejado)**: Visando a tomada de decisão colaborativa entre agentes para execução de tarefas, esse tipo de processo introduz uma abordagem democrática ao gerenciamento de tarefas dentro do CrewAI. Está planejado para desenvolvimento futuro e ainda não está implementado no código-fonte.
 
 ## O Papel dos Processos no Trabalho em Equipe
 Os processos permitem que agentes individuais atuem como uma unidade coesa, otimizando seus esforços para atingir objetivos comuns com eficiência e coerência.
@@ -59,9 +58,9 @@ Emulando uma hierarquia corporativa, o CrewAI permite especificar um agente gere
 
 ## Classe Process: Visão Detalhada
 
-A classe `Process` é implementada como uma enumeração (`Enum`), garantindo segurança de tipo e restringindo os valores de processos aos tipos definidos (`sequential`, `hierarchical`). O processo consensual está planejado para inclusão futura, reforçando nosso compromisso com o desenvolvimento contínuo e a inovação.
+A classe `Process` é implementada como uma enumeração (`Enum`), garantindo segurança de tipo e restringindo os valores de processos aos tipos definidos (`sequential`, `hierarchical`).
 
 ## Conclusão
 
 A colaboração estruturada possibilitada pelos processos dentro do CrewAI é fundamental para permitir o trabalho em equipe sistemático entre agentes.
-Esta documentação foi atualizada para refletir os mais recentes recursos, melhorias e a planejada integração do Processo Consensual, garantindo que os usuários tenham acesso às informações mais atuais e abrangentes.
+Esta documentação foi atualizada para refletir os mais recentes recursos e melhorias, garantindo que os usuários tenham acesso às informações mais atuais e abrangentes.

docs/pt-BR/enterprise/features/agent-control-plane/monitoring.mdx

@@ -6,6 +6,14 @@ icon: "gauge"
 mode: "wide"
 ---
 
+<Info>
+  **Navegação da Documentação do ACP (Beta)**
+
+  - [Visão Geral](/pt-BR/enterprise/features/agent-control-plane/overview)
+  - **Monitoramento** *(você está aqui)*
+  - [Regras](/pt-BR/enterprise/features/agent-control-plane/rules)
+</Info>
+
 ## Visão Geral
 
 A aba **Automações** é a visão de operações somente leitura do [Agent Control Plane](/pt-BR/enterprise/features/agent-control-plane/overview). Ela combina dois cards de métricas, um sankey interativo e duas sub-tabelas — **Automações** e **Consumo** — nas quais você pode buscar, filtrar e ordenar.

docs/pt-BR/enterprise/features/agent-control-plane/overview.mdx

@@ -5,6 +5,14 @@ sidebarTitle: Visão Geral
 icon: "book-open"
 ---
 
+<Info>
+  **Navegação da Documentação do ACP (Beta)**
+
+  - **Visão Geral** *(você está aqui)*
+  - [Monitoramento](/pt-BR/enterprise/features/agent-control-plane/monitoring)
+  - [Regras](/pt-BR/enterprise/features/agent-control-plane/rules)
+</Info>
+
 ## Visão Geral
 
 O **Agent Control Plane** (ACP) é o hub de operações para tudo que você tem rodando no CrewAI AMP. É uma tela única — dividida nas abas **Automações** e **Regras** — que permite à sua equipe:

docs/pt-BR/enterprise/features/agent-control-plane/rules.mdx

@@ -6,6 +6,14 @@ icon: "shield-check"
 mode: "wide"
 ---
 
+<Info>
+  **Navegação da Documentação do ACP (Beta)**
+
+  - [Visão Geral](/pt-BR/enterprise/features/agent-control-plane/overview)
+  - [Monitoramento](/pt-BR/enterprise/features/agent-control-plane/monitoring)
+  - **Regras** *(você está aqui)*
+</Info>
+
 ## Visão Geral
 
 As Regras permitem aplicar políticas — hoje: **PII Redaction** — em muitas automações de uma só vez, em vez de configurar cada deployment individualmente. Abra a aba **Regras** no [Agent Control Plane](/pt-BR/enterprise/features/agent-control-plane/overview) para gerenciá-las.

docs/pt-BR/enterprise/integrations/snowflake.mdx

@@ -0,0 +1,134 @@
+---
+title: Integração com Snowflake
+description: "Conecte agentes CrewAI ao Snowflake Cortex Analyst, Cortex Search e execução SQL através do servidor MCP gerenciado pelo Snowflake."
+icon: "snowflake"
+mode: "wide"
+---
+
+## Visão Geral
+
+Conecte seus agentes CrewAI diretamente aos seus dados no Snowflake através do [servidor MCP gerenciado pelo Snowflake](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp). A integração com o Snowflake permite que seus agentes consultem dados estruturados com **Cortex Analyst**, pesquisem dados não estruturados com **Cortex Search** e executem SQL governado nos seus warehouses — tudo sem escrever ou hospedar nenhum código de conector.
+
+Internamente, a integração com o Snowflake é um wrapper gerenciado em torno do suporte a [Custom MCP Server](/pt-BR/enterprise/guides/custom-mcp-server) do CrewAI. O Snowflake expõe suas capacidades de Cortex AI através de um endpoint [Model Context Protocol](https://modelcontextprotocol.io/), e o CrewAI se conecta a ele de forma segura em seu nome. Qualquer ferramenta que você exponha no lado do Snowflake — Cortex Analyst, Cortex Search, execução SQL, Cortex Agents ou suas próprias ferramentas personalizadas — fica disponível para suas crews.
+
+## Capacidades Principais
+
+<CardGroup cols={3}>
+  <Card title="Cortex Analyst" icon="chart-bar">
+    Faça perguntas em linguagem natural e deixe o [Cortex Analyst](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-analyst) gerar e executar SQL nos seus dados **estruturados** usando modelos semânticos ricos.
+  </Card>
+  <Card title="Cortex Search" icon="magnifying-glass">
+    Recupere dados **não estruturados** relevantes para fluxos de trabalho de RAG e conhecimento com o [Cortex Search](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-search/cortex-search-overview), o serviço de busca totalmente gerenciado do Snowflake.
+  </Card>
+  <Card title="Execução SQL" icon="database">
+    Execute consultas SQL governadas diretamente nos seus warehouses Snowflake, com modo somente leitura configurável, timeouts e seleção de warehouse.
+  </Card>
+</CardGroup>
+
+Como a integração expõe quaisquer ferramentas que seu servidor MCP publica, você também pode expor **Cortex Agents** e **ferramentas personalizadas** (funções definidas pelo usuário e stored procedures) para seus agentes CrewAI.
+
+## Pré-requisitos
+
+Antes de usar a integração com o Snowflake, certifique-se de que você tenha:
+
+- Uma conta [CrewAI AMP](https://app.crewai.com) com assinatura ativa
+- Uma conta Snowflake com acesso aos recursos de Cortex AI
+- Um [servidor MCP gerenciado pelo Snowflake](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp) configurado com as ferramentas que você deseja expor
+- Privilégios Snowflake apropriados (USAGE/SELECT) no servidor MCP e seus objetos subjacentes
+
+## Configurando o Servidor Snowflake MCP
+
+O servidor MCP gerenciado pelo Snowflake é executado dentro da sua conta Snowflake e define quais ferramentas estão disponíveis para clientes externos como o CrewAI. Crie um com o comando [`CREATE MCP SERVER`](https://docs.snowflake.com/en/sql-reference/sql/create-mcp-server), listando os serviços Cortex Search, visualizações semânticas do Cortex Analyst e ferramentas SQL que você deseja expor.
+
+```sql
+CREATE MCP SERVER my_mcp_server
+  FROM SPECIFICATION $$
+    tools:
+      - name: "sales_analyst"
+        type: "CORTEX_ANALYST"
+        identifier: "MY_DATABASE.MY_SCHEMA.sales_semantic_view"
+        description: "Answer questions about sales metrics"
+      - name: "docs_search"
+        type: "CORTEX_SEARCH_SERVICE_QUERY"
+        identifier: "MY_DATABASE.MY_SCHEMA.support_docs_search"
+        description: "Search internal support documentation"
+      - name: "run_sql"
+        type: "SQL_EXECUTION"
+        description: "Execute read-only SQL queries"
+  $$;
+```
+
+<Note>
+O endpoint MCP segue o formato `https://<account_URL>/api/v2/databases/{database}/schemas/{schema}/mcp-servers/{name}`. O CrewAI constrói esta URL automaticamente a partir do **URL da Conta**, **Banco de Dados**, **Schema** e **Nome do Servidor MCP** que você fornece ao configurar a integração.
+</Note>
+
+Para a especificação completa — incluindo Cortex Agents, ferramentas personalizadas, limites de tamanho de resposta e opções de governança — consulte a [documentação do servidor MCP gerenciado pelo Snowflake](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp).
+
+## Conectando o Snowflake no CrewAI AMP
+
+<Frame>
+    <img src="/images/enterprise/snowflake-configure.png" alt="Configurar integração Snowflake no CrewAI AMP" />
+</Frame>
+
+<Steps>
+    <Step title="Abrir Ferramentas e Integrações">
+        Navegue até **Ferramentas e Integrações** na barra lateral esquerda do CrewAI AMP, encontre **Snowflake** na lista de aplicações e abra seu painel de configuração.
+    </Step>
+
+    <Step title="Fornecer detalhes da conexão">
+        Preencha os campos de conexão que o CrewAI usa para acessar seu servidor Snowflake MCP:
+
+        | Campo | Obrigatório | Descrição |
+        |-------|-------------|-----------|
+        | **Nome** | Sim | Um nome descritivo para esta conexão (padrão: `Snowflake`). |
+        | **Descrição** | Não | Um resumo opcional do que esta conexão fornece. |
+        | **URL da Conta** | Sim | A URL da sua conta Snowflake, ex.: `xy12345.us-east-1.snowflakecomputing.com`. |
+        | **Banco de Dados** | Sim | O banco de dados que contém seu servidor MCP (ex.: `MY_DATABASE`). |
+        | **Schema** | Sim | O schema que contém seu servidor MCP (ex.: `MY_SCHEMA`). |
+        | **Nome do Servidor MCP** | Sim | O nome do objeto de servidor MCP que você criou no Snowflake (ex.: `MY_MCP_SERVER`). |
+    </Step>
+
+    <Step title="Escolher um método de autenticação">
+        Selecione como o CrewAI se autentica no Snowflake. **OAuth** é recomendado.
+
+        - **Usar OAuth** — Conecte-se de forma segura usando OAuth 2.0 para autenticação baseada em tokens sem compartilhar suas credenciais. O CrewAI gerencia todo o fluxo de autorização e renova os tokens automaticamente. Copie o **URI de Redirecionamento** mostrado no formulário (`https://oauth.crewai.com/oauth/add`) e registre-o como um URI de redirecionamento autorizado na sua [integração de segurança OAuth](https://docs.snowflake.com/en/user-guide/oauth-custom) do Snowflake.
+        - **Usar token de acesso pessoal** — Autentique usando um [token de acesso programático](https://docs.snowflake.com/en/user-guide/programmatic-access-tokens) gerado nas configurações da sua conta Snowflake. Atribua uma role com privilégios mínimos ao token para limitar a exposição.
+    </Step>
+
+    <Step title="Autenticar">
+        Clique em **Autenticar**. Para OAuth, você será redirecionado ao Snowflake para autorizar o acesso. Após autenticado, o servidor Snowflake aparece na sua lista de Conexões e suas ferramentas ficam disponíveis para suas crews.
+    </Step>
+</Steps>
+
+<Tip>
+Com OAuth, cada usuário se autentica individualmente e as consultas são executadas com seu `DEFAULT_ROLE` do Snowflake. Certifique-se de que os usuários que se conectam tenham uma role e warehouse padrão definidos (`ALTER USER <username> SET DEFAULT_ROLE = '<role>' DEFAULT_WAREHOUSE = '<warehouse>'`) para que as ferramentas Cortex Analyst e SQL tenham capacidade de computação para execução.
+</Tip>
+
+## Usando Ferramentas Snowflake nas Suas Crews
+
+Uma vez conectado, as ferramentas que seu servidor MCP expõe aparecem junto com as conexões integradas na página **Ferramentas e Integrações**. Você pode:
+
+- **Atribuir ferramentas a agentes** nas suas crews como qualquer outra ferramenta CrewAI.
+- **Gerenciar visibilidade** para controlar quais membros do time podem usar a conexão.
+- **Editar ou remover** a conexão a qualquer momento na lista de Conexões.
+
+Seus agentes agora podem solicitar métricas ao Cortex Analyst, executar Cortex Search nos seus documentos e executar SQL — com os resultados fluindo automaticamente para o raciocínio deles.
+
+<Warning>
+O Snowflake impõe governança no servidor MCP: o controle de acesso baseado em roles determina quais ferramentas um usuário pode descobrir e invocar, e limites se aplicam ao tamanho da resposta, contagem de ferramentas (máximo de 50 por servidor) e profundidade de recursão. Se uma chamada de ferramenta falhar, confirme que a role do usuário conectado possui os privilégios necessários no servidor MCP e seus objetos subjacentes.
+</Warning>
+
+## Saiba Mais
+
+<CardGroup cols={2}>
+  <Card title="Servidor MCP Gerenciado pelo Snowflake" icon="snowflake" href="https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-agents-mcp">
+    Documentação oficial do Snowflake para criar e governar o servidor MCP.
+  </Card>
+  <Card title="Servidores Custom MCP no CrewAI" icon="plug" href="/pt-BR/enterprise/guides/custom-mcp-server">
+    Saiba como o CrewAI se conecta a qualquer servidor MCP, a base sobre a qual a integração Snowflake é construída.
+  </Card>
+</CardGroup>
+
+<Card title="Precisa de Ajuda?" icon="headset" href="mailto:support@crewai.com">
+  Entre em contato com nossa equipe de suporte para obter ajuda com a integração Snowflake ou solução de problemas.
+</Card>

lib/cli/pyproject.toml

@@ -8,8 +8,8 @@ authors = [
 ]
 requires-python = ">=3.10, <3.14"
 dependencies = [
-    "crewai-core==1.14.6a2",
-    "click~=8.1.7",
+    "crewai-core==1.14.6",
+    "click>=8.1.7,<9",
     "pydantic>=2.11.9,<2.13",
     "pydantic-settings~=2.10.1",
     "appdirs~=1.4.4",

lib/cli/src/crewai_cli/__init__.py

@@ -1 +1 @@
-__version__ = "1.14.6a2"
+__version__ = "1.14.6"

lib/cli/src/crewai_cli/cli.py

@@ -17,6 +17,7 @@ from crewai_cli.crew_chat import run_chat
 from crewai_cli.deploy.main import DeployCommand
 from crewai_cli.enterprise.main import EnterpriseConfigureCommand
 from crewai_cli.evaluate_crew import evaluate_crew
+from crewai_cli.experimental.skills.main import SkillCommand
 from crewai_cli.install_crew import install_crew
 from crewai_cli.kickoff_flow import kickoff_flow
 from crewai_cli.organization.main import OrganizationCommand
@@ -26,7 +27,6 @@ from crewai_cli.replay_from_task import replay_task_command
 from crewai_cli.reset_memories_command import reset_memories_command
 from crewai_cli.run_crew import run_crew
 from crewai_cli.settings.main import SettingsCommand
-from crewai_cli.skills.main import SkillCommand
 from crewai_cli.task_outputs import load_task_outputs
 from crewai_cli.tools.main import ToolCommand
 from crewai_cli.train_crew import train_crew
@@ -544,8 +544,19 @@ def tool_publish(is_public: bool, force: bool) -> None:
 
 
 @crewai.group()
+def experimental() -> None:
+    """Experimental, unstable commands. Subject to change without notice."""
+    import os
+
+    if os.environ.get("CREWAI_EXPERIMENTAL") != "1":
+        raise click.UsageError(
+            "Experimental commands are gated. Set CREWAI_EXPERIMENTAL=1 to enable."
+        )
+
+
+@experimental.group(name="skill")
 def skill() -> None:
-    """Skill Repository related commands."""
+    """Skill Repository related commands (experimental)."""
 
 
 @skill.command(name="create")

lib/cli/src/crewai_cli/experimental/skills/main.py

@@ -23,9 +23,10 @@ console = Console()
 _SKILL_MD_TEMPLATE = """\
 ---
 name: {name}
-version: 0.1.0
 description: |
   A short description of what this skill does.
+metadata:
+  version: 0.1.0
 ---
 
 ## Instructions
@@ -147,7 +148,7 @@ class SkillCommand(BaseCommand, PlusAPIMixin):
             )
         else:
             try:
-                from crewai.skills.cache import SkillCacheManager
+                from crewai.experimental.skills.cache import SkillCacheManager
 
                 cache = SkillCacheManager()
                 cache.store(org, name, version, archive_bytes)
@@ -191,7 +192,10 @@ class SkillCommand(BaseCommand, PlusAPIMixin):
             raise SystemExit(1) from exc
 
         name = frontmatter.get("name")
-        version = frontmatter.get("version")
+        raw_metadata = frontmatter.get("metadata")
+        version = (
+            raw_metadata.get("version") if isinstance(raw_metadata, dict) else None
+        )
         description = frontmatter.get("description")
 
         if not name:
@@ -362,10 +366,13 @@ class SkillCommand(BaseCommand, PlusAPIMixin):
             return result
 
     def _read_version(self, skill_md: Path) -> str | None:
-        """Read the version field from a SKILL.md file, or None."""
+        """Read the version from a SKILL.md file's metadata, or None."""
         try:
             fm = self._parse_frontmatter(skill_md.read_text())
-            return fm.get("version")
+            raw_metadata = fm.get("metadata")
+            if isinstance(raw_metadata, dict):
+                return raw_metadata.get("version")
+            return None
         except Exception:
             return None
 

lib/cli/tests/experimental/skills/test_main.py

@@ -36,7 +36,7 @@ def skill_command():
             TokenManager().save_tokens(
                 "test-token", (datetime.now() + timedelta(seconds=36000)).timestamp()
             )
-            from crewai_cli.skills.main import SkillCommand
+            from crewai_cli.experimental.skills.main import SkillCommand
             cmd = SkillCommand()
             yield cmd
 
@@ -142,7 +142,7 @@ class TestSkillPublish:
                 mock_resp.status_code = 200
                 mock_resp.json.return_value = {}
                 mock_client.publish_skill.return_value = mock_resp
-                with patch("crewai_cli.skills.main.Settings") as mock_settings_cls:
+                with patch("crewai_cli.experimental.skills.main.Settings") as mock_settings_cls:
                     mock_settings_cls.return_value.org_name = None
                     mock_settings_cls.return_value.enterprise_base_url = None
                     with pytest.raises(SystemExit):
@@ -151,14 +151,14 @@ class TestSkillPublish:
     def test_publish_calls_api(self, skill_command):
         with in_temp_dir():
             Path("SKILL.md").write_text(
-                "---\nname: my-skill\nversion: 1.0.0\ndescription: A test skill.\n---\nInstructions."
+                "---\nname: my-skill\ndescription: A test skill.\nmetadata:\n  version: 1.0.0\n---\nInstructions."
             )
             mock_resp = MagicMock()
             mock_resp.is_success = True
             mock_resp.status_code = 200
             mock_resp.json.return_value = {}
             skill_command.plus_api_client.publish_skill = MagicMock(return_value=mock_resp)
-            with patch("crewai_cli.skills.main.Settings") as mock_settings_cls:
+            with patch("crewai_cli.experimental.skills.main.Settings") as mock_settings_cls:
                 mock_settings_cls.return_value.org_name = "acme"
                 mock_settings_cls.return_value.enterprise_base_url = None
 

lib/crewai-core/src/crewai_core/__init__.py

@@ -1 +1 @@
-__version__ = "1.14.6a2"
+__version__ = "1.14.6"

lib/crewai-files/src/crewai_files/__init__.py

@@ -152,4 +152,4 @@ __all__ = [
     "wrap_file_source",
 ]
 
-__version__ = "1.14.6a2"
+__version__ = "1.14.6"

lib/crewai-tools/pyproject.toml

@@ -10,7 +10,7 @@ requires-python = ">=3.10, <3.14"
 dependencies = [
     "pytube~=15.0.0",
     "requests>=2.33.0,<3",
-    "crewai==1.14.6a2",
+    "crewai==1.14.6",
     "tiktoken>=0.8.0,<0.13",
     "beautifulsoup4~=4.13.4",
     "python-docx~=1.2.0",

lib/crewai-tools/src/crewai_tools/__init__.py

@@ -330,4 +330,4 @@ __all__ = [
     "ZapierActionTools",
 ]
 
-__version__ = "1.14.6a2"
+__version__ = "1.14.6"

lib/crewai/pyproject.toml

@@ -8,8 +8,8 @@ authors = [
 ]
 requires-python = ">=3.10, <3.14"
 dependencies = [
-    "crewai-core==1.14.6a2",
-    "crewai-cli==1.14.6a2",
+    "crewai-core==1.14.6",
+    "crewai-cli==1.14.6",
     # Core Dependencies
     "pydantic>=2.11.9,<2.13",
     "openai>=2.30.0,<3",
@@ -29,7 +29,7 @@ dependencies = [
     "python-dotenv>=1.2.2,<2",
     "pyjwt>=2.9.0,<3",
     # Configuration and Utils
-    "click~=8.1.7",
+    "click>=8.1.7,<9",
     "appdirs~=1.4.4",
     "jsonref~=1.1.0",
     "json-repair~=0.25.2",
@@ -54,7 +54,7 @@ Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.14.6a2",
+    "crewai-tools==1.14.6",
 ]
 embeddings = [
     "tiktoken>=0.8.0,<0.13"

lib/crewai/src/crewai/__init__.py

@@ -48,7 +48,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
 
 _suppress_pydantic_deprecation_warnings()
 
-__version__ = "1.14.6a2"
+__version__ = "1.14.6"
 
 _LAZY_IMPORTS: dict[str, tuple[str, str]] = {
     "Memory": ("crewai.memory.unified_memory", "Memory"),

lib/crewai/src/crewai/agent/core.py

@@ -472,7 +472,7 @@ class Agent(BaseAgent):
 
         for item in items:
             if isinstance(item, str):
-                from crewai.skills.registry import (
+                from crewai.experimental.skills.registry import (
                     is_registry_ref,
                     parse_registry_ref,
                     resolve_registry_ref,

lib/crewai/src/crewai/events/types/skill_events.py

@@ -60,20 +60,3 @@ class SkillLoadFailedEvent(SkillEvent):
 
     type: Literal["skill_load_failed"] = "skill_load_failed"
     error: str
-
-
-class SkillDownloadStartedEvent(SkillEvent):
-    """Event emitted when a registry skill download begins."""
-
-    type: Literal["skill_download_started"] = "skill_download_started"
-    registry_ref: str
-    version: str | None = None
-
-
-class SkillDownloadCompletedEvent(SkillEvent):
-    """Event emitted when a registry skill download completes."""
-
-    type: Literal["skill_download_completed"] = "skill_download_completed"
-    registry_ref: str
-    version: str | None = None
-    cache_path: Path | None = None

lib/crewai/src/crewai/experimental/skills/__init__.py

@@ -0,0 +1,23 @@
+"""Experimental Skills Repository — registry refs, global cache, downloads.
+
+This package contains the registry-backed pieces of the skills feature
+(`@org/name` refs, `~/.crewai/skills/` cache, download events). The stable
+filesystem-based skill loader still lives in `crewai.skills`.
+"""
+
+from crewai.experimental.skills.cache import SkillCacheManager
+from crewai.experimental.skills.registry import (
+    SkillNotCachedError,
+    is_registry_ref,
+    parse_registry_ref,
+    resolve_registry_ref,
+)
+
+
+__all__ = [
+    "SkillCacheManager",
+    "SkillNotCachedError",
+    "is_registry_ref",
+    "parse_registry_ref",
+    "resolve_registry_ref",
+]

lib/crewai/src/crewai/experimental/skills/_flag.py

@@ -0,0 +1,24 @@
+"""Experimental feature gate for the Skills Repository."""
+
+from __future__ import annotations
+
+import os
+
+
+ENV_VAR = "CREWAI_EXPERIMENTAL"
+
+
+class ExperimentalFeatureDisabledError(RuntimeError):
+    """Raised when an experimental feature is used without the flag set."""
+
+
+def is_enabled() -> bool:
+    return os.environ.get(ENV_VAR) == "1"
+
+
+def require_experimental_skills() -> None:
+    if not is_enabled():
+        raise ExperimentalFeatureDisabledError(
+            "The Skills Repository (registry refs, cache, downloads) is "
+            f"experimental. Set {ENV_VAR}=1 to enable it."
+        )

lib/crewai/src/crewai/experimental/skills/events.py

@@ -0,0 +1,30 @@
+"""Download lifecycle events for registry-backed skills.
+
+These events are emitted only by the experimental Skills Repository
+(`@org/name` resolution + global cache). Local-file skill events still
+live in `crewai.events.types.skill_events`.
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Literal
+
+from crewai.events.types.skill_events import SkillEvent
+
+
+class SkillDownloadStartedEvent(SkillEvent):
+    """Event emitted when a registry skill download begins."""
+
+    type: Literal["skill_download_started"] = "skill_download_started"
+    registry_ref: str
+    version: str | None = None
+
+
+class SkillDownloadCompletedEvent(SkillEvent):
+    """Event emitted when a registry skill download completes."""
+
+    type: Literal["skill_download_completed"] = "skill_download_completed"
+    registry_ref: str
+    version: str | None = None
+    cache_path: Path | None = None

lib/crewai/src/crewai/experimental/skills/registry.py

@@ -11,7 +11,7 @@ from pathlib import Path
 import sys
 from typing import Any
 
-from crewai.skills.cache import SkillCacheManager
+from crewai.experimental.skills.cache import SkillCacheManager
 
 
 _logger = logging.getLogger(__name__)
@@ -100,9 +100,11 @@ def resolve_registry_ref(
     Raises:
         SkillNotCachedError: When not cached and running in non-interactive mode.
     """
+    from crewai.experimental.skills._flag import require_experimental_skills
     from crewai.skills.loader import activate_skill
     from crewai.skills.parser import load_skill_metadata
 
+    require_experimental_skills()
     org, name = parse_registry_ref(ref)
 
     local_path = Path.cwd() / "skills" / name
@@ -152,7 +154,7 @@ def download_skill(
 
     try:
         from crewai.events.event_bus import crewai_event_bus
-        from crewai.events.types.skill_events import (
+        from crewai.experimental.skills.events import (
             SkillDownloadCompletedEvent,
             SkillDownloadStartedEvent,
         )

lib/crewai/src/crewai/skills/__init__.py

@@ -3,20 +3,15 @@
 Provides filesystem-based skill packaging with progressive disclosure.
 """
 
-from crewai.skills.cache import SkillCacheManager
 from crewai.skills.loader import activate_skill, discover_skills
 from crewai.skills.models import Skill, SkillFrontmatter
 from crewai.skills.parser import SkillParseError
-from crewai.skills.registry import is_registry_ref, resolve_registry_ref
 
 
 __all__ = [
     "Skill",
-    "SkillCacheManager",
     "SkillFrontmatter",
     "SkillParseError",
     "activate_skill",
     "discover_skills",
-    "is_registry_ref",
-    "resolve_registry_ref",
 ]

lib/crewai/src/crewai/skills/models.py

@@ -49,6 +49,7 @@ class SkillFrontmatter(BaseModel):
         license: Optional license name or reference.
         compatibility: Optional compatibility information (max 500 chars).
         metadata: Optional additional metadata as string key-value pairs.
+            Conventional keys include 'version' (skill semantic version).
         allowed_tools: Optional space-delimited list of pre-approved tools.
     """
 
@@ -71,17 +72,14 @@ class SkillFrontmatter(BaseModel):
     )
     metadata: dict[str, str] | None = Field(
         default=None,
-        description="Arbitrary string key-value pairs for custom skill metadata.",
+        description="Arbitrary string key-value pairs for custom skill metadata. "
+        "Conventional keys include 'version' for the skill's semantic version.",
     )
     allowed_tools: list[str] | None = Field(
         default=None,
         alias="allowed-tools",
         description="Pre-approved tool names the skill may use, parsed from a space-delimited string in frontmatter.",
     )
-    version: str | None = Field(
-        default=None,
-        description="Semantic version of the skill, e.g. '1.0.0'. Optional for local skills.",
-    )
 
     @model_validator(mode="before")
     @classmethod

lib/crewai/tests/experimental/skills/conftest.py

@@ -0,0 +1,6 @@
+import pytest
+
+
+@pytest.fixture(autouse=True)
+def _enable_experimental_skills(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("CREWAI_EXPERIMENTAL", "1")

lib/crewai/tests/experimental/skills/test_cache.py

@@ -8,7 +8,7 @@ import json
 import tarfile
 from pathlib import Path
 
-from crewai.skills.cache import SkillCacheManager
+from crewai.experimental.skills.cache import SkillCacheManager
 
 
 def _make_tar_gz(files: dict[str, str]) -> bytes:

lib/crewai/tests/experimental/skills/test_flag.py

@@ -0,0 +1,30 @@
+"""Tests for the CREWAI_EXPERIMENTAL gate on Skills Repository."""
+
+from __future__ import annotations
+
+import pytest
+
+from crewai.experimental.skills._flag import (
+    ExperimentalFeatureDisabledError,
+    require_experimental_skills,
+)
+from crewai.experimental.skills.registry import resolve_registry_ref
+
+
+def test_require_raises_without_flag(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.delenv("CREWAI_EXPERIMENTAL", raising=False)
+    with pytest.raises(ExperimentalFeatureDisabledError):
+        require_experimental_skills()
+
+
+def test_resolve_registry_ref_raises_without_flag(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    monkeypatch.delenv("CREWAI_EXPERIMENTAL", raising=False)
+    with pytest.raises(ExperimentalFeatureDisabledError):
+        resolve_registry_ref("@acme/my-skill")
+
+
+def test_require_passes_with_flag(monkeypatch: pytest.MonkeyPatch) -> None:
+    monkeypatch.setenv("CREWAI_EXPERIMENTAL", "1")
+    require_experimental_skills()

lib/crewai/tests/experimental/skills/test_models_version.py

@@ -0,0 +1,32 @@
+"""Tests for the 'version' metadata key on SkillFrontmatter.
+
+Per the agentskills.io spec, `version` lives under `metadata`, not as a
+top-level frontmatter field.
+"""
+
+from __future__ import annotations
+
+from crewai.skills.models import SkillFrontmatter
+
+
+class TestSkillFrontmatterVersion:
+    def test_no_metadata_by_default(self) -> None:
+        fm = SkillFrontmatter(name="my-skill", description="A skill.")
+        assert fm.metadata is None
+
+    def test_version_via_metadata(self) -> None:
+        fm = SkillFrontmatter(
+            name="my-skill",
+            description="A skill.",
+            metadata={"version": "1.2.3"},
+        )
+        assert fm.metadata is not None
+        assert fm.metadata["version"] == "1.2.3"
+
+    def test_metadata_accepts_other_keys(self) -> None:
+        fm = SkillFrontmatter(
+            name="my-skill",
+            description="A skill.",
+            metadata={"version": "1.0.0", "author": "acme"},
+        )
+        assert fm.metadata == {"version": "1.0.0", "author": "acme"}

lib/crewai/tests/experimental/skills/test_registry.py

@@ -5,7 +5,7 @@ from __future__ import annotations
 from pathlib import Path
 from unittest.mock import MagicMock, patch
 
-from crewai.skills.registry import (
+from crewai.experimental.skills.registry import (
     SkillNotCachedError,
     is_registry_ref,
     parse_registry_ref,
@@ -75,11 +75,11 @@ class TestResolveRegistryRef:
         mock_cache.get_cached_path.return_value = None
 
         with (
-            patch("crewai.skills.registry._is_noninteractive", return_value=False),
+            patch("crewai.experimental.skills.registry._is_noninteractive", return_value=False),
             patch.object(Path, "cwd", return_value=tmp_path),
-            patch("crewai.skills.registry.SkillCacheManager", return_value=mock_cache),
+            patch("crewai.experimental.skills.registry.SkillCacheManager", return_value=mock_cache),
         ):
-            from crewai.skills.registry import resolve_registry_ref
+            from crewai.experimental.skills.registry import resolve_registry_ref
             skill = resolve_registry_ref("@acme/my-skill")
 
         assert skill.name == "my-skill"
@@ -90,11 +90,11 @@ class TestResolveRegistryRef:
         mock_cache.get_cached_path.return_value = None
 
         with (
-            patch("crewai.skills.registry._is_noninteractive", return_value=True),
+            patch("crewai.experimental.skills.registry._is_noninteractive", return_value=True),
             patch.object(Path, "cwd", return_value=tmp_path),
-            patch("crewai.skills.registry.SkillCacheManager", return_value=mock_cache),
+            patch("crewai.experimental.skills.registry.SkillCacheManager", return_value=mock_cache),
         ):
-            from crewai.skills.registry import resolve_registry_ref
+            from crewai.experimental.skills.registry import resolve_registry_ref
             with pytest.raises(SkillNotCachedError) as exc_info:
                 resolve_registry_ref("@acme/ghost-skill")
             assert "@acme/ghost-skill" in str(exc_info.value)
@@ -112,11 +112,11 @@ class TestResolveRegistryRef:
 
         # tmp_path has no ./skills/ directory
         with (
-            patch("crewai.skills.registry._is_noninteractive", return_value=False),
+            patch("crewai.experimental.skills.registry._is_noninteractive", return_value=False),
             patch.object(Path, "cwd", return_value=tmp_path),
-            patch("crewai.skills.registry.SkillCacheManager", return_value=mock_cache),
+            patch("crewai.experimental.skills.registry.SkillCacheManager", return_value=mock_cache),
         ):
-            from crewai.skills.registry import resolve_registry_ref
+            from crewai.experimental.skills.registry import resolve_registry_ref
             skill = resolve_registry_ref("@acme/cached-skill")
 
         assert skill.name == "cached-skill"

lib/crewai/tests/skills/test_models_version.py

@@ -1,32 +0,0 @@
-"""Tests for the version field added to SkillFrontmatter."""
-
-from __future__ import annotations
-
-import pytest
-from pydantic import ValidationError
-
-from crewai.skills.models import SkillFrontmatter
-
-
-class TestSkillFrontmatterVersion:
-    def test_version_defaults_to_none(self) -> None:
-        fm = SkillFrontmatter(name="my-skill", description="A skill.")
-        assert fm.version is None
-
-    def test_version_can_be_set(self) -> None:
-        fm = SkillFrontmatter(name="my-skill", description="A skill.", version="1.2.3")
-        assert fm.version == "1.2.3"
-
-    def test_existing_frontmatter_without_version_still_valid(self) -> None:
-        """Backward compat: existing SKILL.md files without version must still parse."""
-        fm = SkillFrontmatter(name="old-skill", description="Old skill without version.")
-        assert fm.version is None
-
-    def test_version_is_optional_string(self) -> None:
-        fm = SkillFrontmatter(name="my-skill", description="Desc.", version=None)
-        assert fm.version is None
-
-    def test_frontmatter_is_frozen(self) -> None:
-        fm = SkillFrontmatter(name="my-skill", description="A skill.", version="1.0.0")
-        with pytest.raises(ValidationError):
-            fm.version = "2.0.0"  # type: ignore[misc]

lib/devtools/pyproject.toml

@@ -10,7 +10,7 @@ requires-python = ">=3.10, <3.14"
 classifiers = ["Private :: Do Not Upload"]
 private = true
 dependencies = [
-    "click~=8.1.7",
+    "click>=8.1.7,<9",
     "tomlkit~=0.13.2",
     "openai>=1.83.0,<3",
     "python-dotenv>=1.2.2,<2",

lib/devtools/src/crewai_devtools/__init__.py

@@ -1,3 +1,3 @@
 """CrewAI development tools."""
 
-__version__ = "1.14.6a2"
+__version__ = "1.14.6"

pyproject.toml

@@ -181,7 +181,7 @@ exclude-newer = "3 days"
 # transformers 4.57.6 has CVE-2026-1839; force 5.4+ (docling 2.84 allows huggingface-hub>=1).
 # cryptography 46.0.6 has CVE-2026-39892; force 46.0.7+.
 # pypdf <6.10.2 has GHSA-4pxv-j86v-mhcw, GHSA-7gw9-cf7v-778f, GHSA-x284-j5p8-9c5p; force 6.10.2+.
-# uv <0.11.6 has GHSA-pjjw-68hj-v9mw; force 0.11.6+.
+# uv <0.11.15 has GHSA-4gg8-gxpx-9rph (and earlier GHSA-pjjw-68hj-v9mw); force 0.11.15+.
 # python-multipart <0.0.27 has GHSA-pp6c-gr5w-3c5g (DoS via unbounded multipart headers).
 # gitpython <3.1.50 has GHSA-mv93-w799-cj2w (config_writer newline injection bypassing the 3.1.49 patch -> RCE via core.hooksPath).
 # urllib3 <2.7.0 has GHSA-qccp-gfcp-xxvc (ProxyManager cross-origin redirect leaks Authorization/Cookie) and GHSA-mf9v-mfxr-j63j (streaming decompression-bomb bypass); force 2.7.0+.
@@ -203,7 +203,7 @@ override-dependencies = [
     "transformers>=5.4.0; python_version >= '3.10'",
     "cryptography>=46.0.7",
     "pypdf>=6.10.2,<7",
-    "uv>=0.11.6,<1",
+    "uv>=0.11.15,<1",
     "python-multipart>=0.0.27,<1",
     "gitpython>=3.1.50,<4",
     "langsmith>=0.8.0,<1",

uv.lock

@@ -13,12 +13,9 @@ resolution-markers = [
 ]
 
 [options]
-exclude-newer = "2026-05-19T15:27:50.647689Z"
+exclude-newer = "2026-05-29T06:38:49.259217Z"
 exclude-newer-span = "P3D"
 
-[options.exclude-newer-package]
-starlette = "2026-05-22T16:00:00Z"
-
 [manifest]
 members = [
     "crewai",
@@ -46,7 +43,7 @@ overrides = [
     { name = "starlette", specifier = ">=1.0.1" },
     { name = "transformers", marker = "python_full_version >= '3.10'", specifier = ">=5.4.0" },
     { name = "urllib3", specifier = ">=2.7.0" },
-    { name = "uv", specifier = ">=0.11.6,<1" },
+    { name = "uv", specifier = ">=0.11.15,<1" },
 ]
 
 [manifest.dependency-groups]
@@ -9449,28 +9446,28 @@ wheels = [
 
 [[package]]
 name = "uv"
-version = "0.11.7"
+version = "0.11.17"
 source = { registry = "https://pypi.org/simple" }
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