feat: remove --public/--private flags from tool publish command

All tools are now private to the organization by default. The --public and --private CLI flags have been removed along with the is_public parameter throughout the stack. Docs updated across EN, PT-BR, and KO.
docs: update changelog and version for v1.11.0
2026-10-22 01:43:13 +02:00 · 2026-03-18 13:28:59 -03:00 · 2026-03-18 09:38:38 -04:00 · 2026-03-18 09:30:05 -04:00 · 2026-03-17 17:07:26 -04:00 · 2026-03-17 16:58:59 -04:00
39 changed files with 2291 additions and 163 deletions
@@ -43,6 +43,35 @@ def _patched_make_vcr_request(httpx_request: Any, **kwargs: Any) -> Any:
 httpx_stubs._make_vcr_request = _patched_make_vcr_request


+# Patch the response-side of VCR to fix httpx.ResponseNotRead errors.
+# VCR's _from_serialized_response mocks httpx.Response.read(), which prevents
+# the response's internal _content attribute from being properly initialized.
+# When OpenAI's client (using with_raw_response) accesses response.content,
+# httpx raises ResponseNotRead because read() was never actually called.
+# This patch ensures _content is explicitly set after response creation.
+_original_from_serialized_response = getattr(
+    httpx_stubs, "_from_serialized_response", None
+)
+
+if _original_from_serialized_response is not None:
+
+    def _patched_from_serialized_response(
+        request: Any, serialized_response: Any, history: Any = None
+    ) -> Any:
+        """Patched version that ensures response._content is properly set."""
+        response = _original_from_serialized_response(request, serialized_response, history)
+        # Explicitly set _content to avoid ResponseNotRead errors
+        # The content was passed to the constructor but the mocked read() prevents
+        # proper initialization of the internal state
+        body_content = serialized_response.get("body", {}).get("string", b"")
+        if isinstance(body_content, str):
+            body_content = body_content.encode("utf-8")
+        response._content = body_content
+        return response
+
+    httpx_stubs._from_serialized_response = _patched_from_serialized_response
+
+
@pytest.fixture(autouse=True, scope="function")
 def cleanup_event_handlers() -> Generator[None, Any, None]:
    """Clean up event bus handlers after each test to prevent test pollution."""
@@ -4,6 +4,47 @@ description: "Product updates, improvements, and bug fixes for CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="Mar 18, 2026">
+  ## v1.11.0
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.11.0)
+
+  ## What's Changed
+
+  ### Documentation
+  - Update changelog and version for v1.11.0rc2
+
+  ## Contributors
+
+  @greysonlalonde
+
+</Update>
+
+<Update label="Mar 17, 2026">
+  ## v1.11.0rc2
+
+  [View release on GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.11.0rc2)
+
+  ## What's Changed
+
+  ### Bug Fixes
+  - Enhance LLM response handling and serialization.
+  - Upgrade vulnerable transitive dependencies (authlib, PyJWT, snowflake-connector-python).
+  - Replace `os.system` with `subprocess.run` in unsafe mode pip install.
+
+  ### Documentation
+  - Update Exa Search Tool page with improved naming, description, and configuration options.
+  - Add Custom MCP Servers in How-To Guide.
+  - Update OTEL collectors documentation.
+  - Update MCP documentation.
+  - Update changelog and version for v1.11.0rc1.
+
+  ## Contributors
+
+  @10ishq, @greysonlalonde, @joaomdmoura, @lucasgomide, @mattatcha, @theCyberTech, @vinibrsl
+
+</Update>
+
 <Update label="Mar 15, 2026">
  ## v1.11.0rc1

@@ -1,30 +1,39 @@
 ---
-title: "Open Telemetry Logs"
-description: "Understand how to capture telemetry logs from your CrewAI AMP deployments"
+title: "OpenTelemetry Export"
+description: "Export traces and logs from your CrewAI AMP deployments to your own OpenTelemetry collector"
 icon: "magnifying-glass-chart"
 mode: "wide"
 ---

-CrewAI AMP provides a powerful way to capture telemetry logs from your deployments. This allows you to monitor the performance of your agents and workflows, and to debug issues that may arise.
+CrewAI AMP can export OpenTelemetry **traces** and **logs** from your deployments directly to your own collector. This lets you monitor agent performance, track LLM calls, and debug issues using your existing observability stack.
+
+Telemetry data follows the [OpenTelemetry GenAI semantic conventions](https://opentelemetry.io/docs/specs/semconv/gen-ai/) plus additional CrewAI-specific attributes.

 ## Prerequisites

 <CardGroup cols={2}>
-  <Card title="ENTERPRISE OTEL SETUP enabled" icon="users">
-    Your organization should have ENTERPRISE OTEL SETUP enabled
+  <Card title="CrewAI AMP account" icon="users">
+    Your organization must have an active CrewAI AMP account.
  </Card>
-  <Card title="OTEL collector setup" icon="server">
-    Your organization should have an OTEL collector setup or a provider like
-    Datadog log intake setup
+  <Card title="OpenTelemetry collector" icon="server">
+    You need an OpenTelemetry-compatible collector endpoint (e.g., your own OTel Collector, Datadog, Grafana, or any OTLP-compatible backend).
  </Card>
 </CardGroup>

-## How to capture telemetry logs
+## Setting up a collector

-1. Go to settings/organization tab
-2. Configure your OTEL collector setup
-3. Save
+1. In CrewAI AMP, go to **Settings** > **OpenTelemetry Collectors**.
+2. Click **Add Collector**.
+3. Select an integration type — **OpenTelemetry Traces** or **OpenTelemetry Logs**.
+4. Configure the connection:
+   - **Endpoint** — Your collector's OTLP endpoint (e.g., `https://otel-collector.example.com:4317`).
+   - **Service Name** — A name to identify this service in your observability platform.
+   - **Custom Headers** *(optional)* — Add authentication or routing headers as key-value pairs.
+   - **Certificate** *(optional)* — Provide a TLS certificate if your collector requires one.
+5. Click **Save**.

-Example to setup OTEL log collection capture to Datadog.
+<Frame>![OpenTelemetry Collector Configuration](/images/crewai-otel-collector-config.png)</Frame>

-<Frame>![Capture Telemetry Logs](/images/crewai-otel-export.png)</Frame>
+<Tip>
+  You can add multiple collectors — for example, one for traces and another for logs, or send to different backends for different purposes.
+</Tip>
@@ -0,0 +1,136 @@
+---
+title: "Custom MCP Servers"
+description: "Connect your own MCP servers to CrewAI AMP with public access, API key authentication, or OAuth 2.0"
+icon: "plug"
+mode: "wide"
+---
+
+CrewAI AMP supports connecting to any MCP server that implements the [Model Context Protocol](https://modelcontextprotocol.io/). You can bring public servers that require no authentication, servers protected by an API key or bearer token, and servers that use OAuth 2.0 for secure delegated access.
+
+## Prerequisites
+
+<CardGroup cols={2}>
+  <Card title="CrewAI AMP Account" icon="user">
+    You need an active [CrewAI AMP](https://app.crewai.com) account.
+  </Card>
+  <Card title="MCP Server URL" icon="link">
+    The URL of the MCP server you want to connect. The server must be accessible from the internet and support Streamable HTTP transport.
+  </Card>
+</CardGroup>
+
+## Adding a Custom MCP Server
+
+<Steps>
+    <Step title="Open Tools & Integrations">
+        Navigate to **Tools & Integrations** in the left sidebar of CrewAI AMP, then select the **Connections** tab.
+    </Step>
+
+    <Step title="Start adding a Custom MCP Server">
+        Click the **Add Custom MCP Server** button. A dialog will appear with the configuration form.
+    </Step>
+
+    <Step title="Fill in the basic information">
+        - **Name** (required): A descriptive name for your MCP server (e.g., "My Internal Tools Server").
+        - **Description**: An optional summary of what this MCP server provides.
+        - **Server URL** (required): The full URL to your MCP server endpoint (e.g., `https://my-server.example.com/mcp`).
+    </Step>
+
+    <Step title="Choose an authentication method">
+        Select one of the three available authentication methods based on how your MCP server is secured. See the sections below for details on each method.
+    </Step>
+
+    <Step title="Add custom headers (optional)">
+        If your MCP server requires additional headers on every request (e.g., tenant identifiers or routing headers), click **+ Add Header** and provide the header name and value. You can add multiple custom headers.
+    </Step>
+
+    <Step title="Create the connection">
+        Click **Create MCP Server** to save the connection. Your custom MCP server will now appear in the Connections list and its tools will be available for use in your crews.
+    </Step>
+</Steps>
+
+## Authentication Methods
+
+### No Authentication
+
+Choose this option when your MCP server is publicly accessible and does not require any credentials. This is common for open-source or internal servers running behind a VPN.
+
+### Authentication Token
+
+Use this method when your MCP server is protected by an API key or bearer token.
+
+<Frame>
+    <img src="/images/enterprise/custom-mcp-auth-token.png" alt="Custom MCP Server with Authentication Token" />
+</Frame>
+
+| Field | Required | Description |
+|-------|----------|-------------|
+| **Header Name** | Yes | The name of the HTTP header that carries the token (e.g., `X-API-Key`, `Authorization`). |
+| **Value** | Yes | Your API key or bearer token. |
+| **Add to** | No | Where to attach the credential — **Header** (default) or **Query parameter**. |
+
+<Tip>
+If your server expects a `Bearer` token in the `Authorization` header, set the Header Name to `Authorization` and the Value to `Bearer <your-token>`.
+</Tip>
+
+### OAuth 2.0
+
+Use this method for MCP servers that require OAuth 2.0 authorization. CrewAI will handle the full OAuth flow, including token refresh.
+
+<Frame>
+    <img src="/images/enterprise/custom-mcp-oauth.png" alt="Custom MCP Server with OAuth 2.0" />
+</Frame>
+
+| Field | Required | Description |
+|-------|----------|-------------|
+| **Redirect URI** | — | Pre-filled and read-only. Copy this URI and register it as an authorized redirect URI in your OAuth provider. |
+| **Authorization Endpoint** | Yes | The URL where users are sent to authorize access (e.g., `https://auth.example.com/oauth/authorize`). |
+| **Token Endpoint** | Yes | The URL used to exchange the authorization code for an access token (e.g., `https://auth.example.com/oauth/token`). |
+| **Client ID** | Yes | The OAuth client ID issued by your provider. |
+| **Client Secret** | No | The OAuth client secret. Not required for public clients using PKCE. |
+| **Scopes** | No | Space-separated list of scopes to request (e.g., `read write`). |
+| **Token Auth Method** | No | How the client credentials are sent when exchanging tokens — **Standard (POST body)** or **Basic Auth (header)**. Defaults to Standard. |
+| **PKCE Supported** | No | Enable if your OAuth provider supports Proof Key for Code Exchange. Recommended for improved security. |
+
+<Info>
+**Discover OAuth Config**: If your OAuth provider supports OpenID Connect Discovery, click the **Discover OAuth Config** link to auto-populate the authorization and token endpoints from the provider's `/.well-known/openid-configuration` URL.
+</Info>
+
+#### Setting Up OAuth 2.0 Step by Step
+
+<Steps>
+    <Step title="Register the redirect URI">
+        Copy the **Redirect URI** shown in the form and add it as an authorized redirect URI in your OAuth provider's application settings.
+    </Step>
+
+    <Step title="Enter endpoints and credentials">
+        Fill in the **Authorization Endpoint**, **Token Endpoint**, **Client ID**, and optionally the **Client Secret** and **Scopes**.
+    </Step>
+
+    <Step title="Configure token exchange method">
+        Select the appropriate **Token Auth Method**. Most providers use the default **Standard (POST body)**. Some older providers require **Basic Auth (header)**.
+    </Step>
+
+    <Step title="Enable PKCE (recommended)">
+        Check **PKCE Supported** if your provider supports it. PKCE adds an extra layer of security to the authorization code flow and is recommended for all new integrations.
+    </Step>
+
+    <Step title="Create and authorize">
+        Click **Create MCP Server**. You will be redirected to your OAuth provider to authorize access. Once authorized, CrewAI will store the tokens and automatically refresh them as needed.
+    </Step>
+</Steps>
+
+## Using Your Custom MCP Server
+
+Once connected, your custom MCP server's tools 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 server.
+- **Edit or remove** the connection at any time from the Connections list.
+
+<Warning>
+If your MCP server becomes unreachable or the credentials expire, tool calls using that server will fail. Make sure the server URL is stable and credentials are kept up to date.
+</Warning>
+
+<Card title="Need Help?" icon="headset" href="mailto:support@crewai.com">
+  Contact our support team for assistance with custom MCP server configuration or troubleshooting.
+</Card>
@@ -9,10 +9,7 @@ mode: "wide"

 The Tool Repository is a package manager for CrewAI tools. It allows users to publish, install, and manage tools that integrate with CrewAI crews and flows.

-Tools can be:
-
- **Private**: accessible only within your organization (default)
- **Public**: accessible to all CrewAI users if published with the `--public` flag
+All tools are private by default and accessible only within your organization.

 The repository is not a version control system. Use Git to track code changes and enable collaboration.

@@ -106,12 +103,6 @@ To publish the tool:
 crewai tool publish
 ```

-By default, tools are published as private. To make a tool public:
-
-```bash
-crewai tool publish --public
-```
-
 For more details on how to build tools, see [Creating your own tools](/en/concepts/tools#creating-your-own-tools).

 ## Updating Tools
@@ -1,53 +1,110 @@
 ---
-title: EXA Search Web Loader
-description: The `EXASearchTool` is designed to perform a semantic search for a specified query from a text's content across the internet.
-icon: globe-pointer
+title: "Exa Search Tool"
+description: "Search the web using the Exa Search API to find the most relevant results for any query, with options for full page content, highlights, and summaries."
+icon: "magnifying-glass"
 mode: "wide"
 ---

-# `EXASearchTool`
-
-## Description
-
-The EXASearchTool is designed to perform a semantic search for a specified query from a text's content across the internet. 
-It utilizes the [exa.ai](https://exa.ai/) API to fetch and display the most relevant search results based on the query provided by the user.
+The `EXASearchTool` lets CrewAI agents search the web using the [Exa](https://exa.ai/) search API. It returns the most relevant results for any query, with options for full page content and AI-generated summaries.

 ## Installation

-To incorporate this tool into your project, follow the installation instructions below:
+Install the CrewAI tools package:

 ```shell
 pip install 'crewai[tools]'
 ```

-## Example
+## Environment Variables

-The following example demonstrates how to initialize the tool and execute a search with a given query:
+Set your Exa API key as an environment variable:

-```python Code
-from crewai_tools import EXASearchTool
-
-# Initialize the tool for internet searching capabilities
-tool = EXASearchTool()
+```bash
+export EXA_API_KEY='your_exa_api_key'
 ```

-## Steps to Get Started
+Get an API key from the [Exa dashboard](https://dashboard.exa.ai/api-keys).

-To effectively use the EXASearchTool, follow these steps:
+## Example Usage

-<Steps>
-    <Step title="Package Installation">
-        Confirm that the `crewai[tools]` package is installed in your Python environment.
-    </Step>
-    <Step title="API Key Acquisition">
-        Acquire a [exa.ai](https://exa.ai/) API key by registering for a free account at [exa.ai](https://exa.ai/).
-    </Step>
-    <Step title="Environment Configuration">
-        Store your obtained API key in an environment variable named `EXA_API_KEY` to facilitate its use by the tool.
-    </Step>
-</Steps>
+Here's how to use the `EXASearchTool` within a CrewAI agent:

-## Conclusion
+```python
+import os
+from crewai import Agent, Task, Crew
+from crewai_tools import EXASearchTool

-By integrating the `EXASearchTool` into Python projects, users gain the ability to conduct real-time, relevant searches across the internet directly from their applications. 
-By adhering to the setup and usage guidelines provided, incorporating this tool into projects is streamlined and straightforward.
+# Initialize the tool
+exa_tool = EXASearchTool()
+
+# Create an agent that uses the tool
+researcher = Agent(
+    role='Research Analyst',
+    goal='Find the latest information on any topic',
+    backstory='An expert researcher who finds the most relevant and up-to-date information.',
+    tools=[exa_tool],
+    verbose=True
+)
+
+# Create a task for the agent
+research_task = Task(
+    description='Find the top 3 recent breakthroughs in quantum computing.',
+    expected_output='A summary of the top 3 breakthroughs with source URLs.',
+    agent=researcher
+)
+
+# Form the crew and kick it off
+crew = Crew(
+    agents=[researcher],
+    tasks=[research_task],
+    verbose=True
+)
+
+result = crew.kickoff()
+print(result)
+```
+
+## Configuration Options
+
+The `EXASearchTool` accepts the following parameters during initialization:
+
+- `type` (str, optional): The search type to use. Defaults to `"auto"`. Options: `"auto"`, `"instant"`, `"fast"`, `"deep"`.
+- `content` (bool, optional): Whether to include full page content in results. Defaults to `False`.
+- `summary` (bool, optional): Whether to include AI-generated summaries of each result. Requires `content=True`. Defaults to `False`.
+- `api_key` (str, optional): Your Exa API key. Falls back to the `EXA_API_KEY` environment variable if not provided.
+- `base_url` (str, optional): Custom API server URL. Falls back to the `EXA_BASE_URL` environment variable if not provided.
+
+When calling the tool (or when an agent invokes it), the following search parameters are available:
+
+- `search_query` (str): **Required**. The search query string.
+- `start_published_date` (str, optional): Filter results published after this date (ISO 8601 format, e.g. `"2024-01-01"`).
+- `end_published_date` (str, optional): Filter results published before this date (ISO 8601 format).
+- `include_domains` (list[str], optional): A list of domains to restrict the search to.
+
+## Advanced Usage
+
+You can configure the tool with custom parameters for richer results:
+
+```python
+# Get full page content with AI summaries
+exa_tool = EXASearchTool(
+    content=True,
+    summary=True,
+    type="deep"
+)
+
+# Use it in an agent
+agent = Agent(
+    role="Deep Researcher",
+    goal="Conduct thorough research with full content and summaries",
+    tools=[exa_tool]
+)
+```
+
+## Features
+
+- **Semantic Search**: Find results based on meaning, not just keywords
+- **Full Content Retrieval**: Get the full text of web pages alongside search results
+- **AI Summaries**: Get concise, AI-generated summaries of each result
+- **Date Filtering**: Limit results to specific time periods with published date filters
+- **Domain Filtering**: Restrict searches to specific domains
@@ -4,6 +4,47 @@ description: "CrewAI의 제품 업데이트, 개선 사항 및 버그 수정"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="2026년 3월 18일">
+  ## v1.11.0
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.11.0)
+
+  ## 변경 사항
+
+  ### 문서
+  - v1.11.0rc2에 대한 변경 로그 및 버전 업데이트
+
+  ## 기여자
+
+  @greysonlalonde
+
+</Update>
+
+<Update label="2026년 3월 17일">
+  ## v1.11.0rc2
+
+  [GitHub 릴리스 보기](https://github.com/crewAIInc/crewAI/releases/tag/1.11.0rc2)
+
+  ## 변경 사항
+
+  ### 버그 수정
+  - LLM 응답 처리 및 직렬화 개선.
+  - 취약한 전이 종속성(authlib, PyJWT, snowflake-connector-python) 업그레이드.
+  - 안전하지 않은 모드에서 pip 설치 시 `os.system`을 `subprocess.run`으로 교체.
+
+  ### 문서
+  - 개선된 이름, 설명 및 구성 옵션으로 Exa 검색 도구 페이지 업데이트.
+  - 사용 방법 가이드에 사용자 지정 MCP 서버 추가.
+  - OTEL 수집기 문서 업데이트.
+  - MCP 문서 업데이트.
+  - v1.11.0rc1에 대한 변경 로그 및 버전 업데이트.
+
+  ## 기여자
+
+  @10ishq, @greysonlalonde, @joaomdmoura, @lucasgomide, @mattatcha, @theCyberTech, @vinibrsl
+
+</Update>
+
 <Update label="2026년 3월 15일">
  ## v1.11.0rc1

@@ -0,0 +1,39 @@
+---
+title: "OpenTelemetry 내보내기"
+description: "CrewAI AMP 배포에서 자체 OpenTelemetry 수집기로 트레이스와 로그를 내보내기"
+icon: "magnifying-glass-chart"
+mode: "wide"
+---
+
+CrewAI AMP는 배포에서 OpenTelemetry **트레이스**와 **로그**를 자체 수집기로 직접 내보낼 수 있습니다. 이를 통해 기존 관측 가능성 스택을 사용하여 에이전트 성능을 모니터링하고, LLM 호출을 추적하고, 문제를 디버깅할 수 있습니다.
+
+텔레메트리 데이터는 [OpenTelemetry GenAI 시맨틱 규칙](https://opentelemetry.io/docs/specs/semconv/gen-ai/)과 추가적인 CrewAI 전용 속성을 따릅니다.
+
+## 사전 요구 사항
+
+<CardGroup cols={2}>
+  <Card title="CrewAI AMP 계정" icon="users">
+    조직에 활성 CrewAI AMP 계정이 있어야 합니다.
+  </Card>
+  <Card title="OpenTelemetry 수집기" icon="server">
+    OpenTelemetry 호환 수집기 엔드포인트가 필요합니다 (예: 자체 OTel Collector, Datadog, Grafana 또는 OTLP 호환 백엔드).
+  </Card>
+</CardGroup>
+
+## 수집기 설정
+
+1. CrewAI AMP에서 **Settings** > **OpenTelemetry Collectors**로 이동합니다.
+2. **Add Collector**를 클릭합니다.
+3. 통합 유형을 선택합니다 — **OpenTelemetry Traces** 또는 **OpenTelemetry Logs**.
+4. 연결을 구성합니다:
+   - **Endpoint** — 수집기의 OTLP 엔드포인트 (예: `https://otel-collector.example.com:4317`).
+   - **Service Name** — 관측 가능성 플랫폼에서 이 서비스를 식별하기 위한 이름.
+   - **Custom Headers** *(선택 사항)* — 인증 또는 라우팅 헤더를 키-값 쌍으로 추가합니다.
+   - **Certificate** *(선택 사항)* — 수집기에서 TLS 인증서가 필요한 경우 제공합니다.
+5. **Save**를 클릭합니다.
+
+<Frame>![OpenTelemetry 수집기 구성](/images/crewai-otel-collector-config.png)</Frame>
+
+<Tip>
+  여러 수집기를 추가할 수 있습니다 — 예를 들어, 트레이스용 하나와 로그용 하나를 추가하거나, 다른 목적을 위해 다른 백엔드로 전송할 수 있습니다.
+</Tip>
@@ -0,0 +1,136 @@
+---
+title: "커스텀 MCP 서버"
+description: "공개 액세스, API 키 인증 또는 OAuth 2.0을 사용하여 자체 MCP 서버를 CrewAI AMP에 연결하세요"
+icon: "plug"
+mode: "wide"
+---
+
+CrewAI AMP는 [Model Context Protocol](https://modelcontextprotocol.io/)을 구현하는 모든 MCP 서버에 연결할 수 있습니다. 인증이 필요 없는 공개 서버, API 키 또는 Bearer 토큰으로 보호되는 서버, OAuth 2.0을 사용하는 서버를 연결할 수 있습니다.
+
+## 사전 요구사항
+
+<CardGroup cols={2}>
+  <Card title="CrewAI AMP 계정" icon="user">
+    활성화된 [CrewAI AMP](https://app.crewai.com) 계정이 필요합니다.
+  </Card>
+  <Card title="MCP 서버 URL" icon="link">
+    연결하려는 MCP 서버의 URL입니다. 서버는 인터넷에서 접근 가능해야 하며 Streamable HTTP 전송을 지원해야 합니다.
+  </Card>
+</CardGroup>
+
+## 커스텀 MCP 서버 추가하기
+
+<Steps>
+    <Step title="Tools & Integrations 열기">
+        CrewAI AMP 왼쪽 사이드바에서 **Tools & Integrations**로 이동한 후 **Connections** 탭을 선택합니다.
+    </Step>
+
+    <Step title="커스텀 MCP 서버 추가 시작">
+        **Add Custom MCP Server** 버튼을 클릭합니다. 구성 양식이 포함된 대화 상자가 나타납니다.
+    </Step>
+
+    <Step title="기본 정보 입력">
+        - **Name** (필수): MCP 서버의 설명적 이름 (예: "내부 도구 서버").
+        - **Description**: 이 MCP 서버가 제공하는 기능에 대한 선택적 요약.
+        - **Server URL** (필수): MCP 서버 엔드포인트의 전체 URL (예: `https://my-server.example.com/mcp`).
+    </Step>
+
+    <Step title="인증 방법 선택">
+        MCP 서버의 보안 방식에 따라 세 가지 인증 방법 중 하나를 선택합니다. 각 방법에 대한 자세한 내용은 아래 섹션을 참조하세요.
+    </Step>
+
+    <Step title="커스텀 헤더 추가 (선택사항)">
+        MCP 서버가 모든 요청에 추가 헤더를 요구하는 경우 (예: 테넌트 식별자 또는 라우팅 헤더), **+ Add Header**를 클릭하고 헤더 이름과 값을 입력합니다. 여러 커스텀 헤더를 추가할 수 있습니다.
+    </Step>
+
+    <Step title="연결 생성">
+        **Create MCP Server**를 클릭하여 연결을 저장합니다. 커스텀 MCP 서버가 Connections 목록에 나타나고 해당 도구를 crew에서 사용할 수 있게 됩니다.
+    </Step>
+</Steps>
+
+## 인증 방법
+
+### 인증 없음
+
+MCP 서버가 공개적으로 접근 가능하고 자격 증명이 필요 없을 때 이 옵션을 선택합니다. 오픈 소스 서버나 VPN 뒤에서 실행되는 내부 서버에 일반적입니다.
+
+### 인증 토큰
+
+MCP 서버가 API 키 또는 Bearer 토큰으로 보호되는 경우 이 방법을 사용합니다.
+
+<Frame>
+    <img src="/images/enterprise/custom-mcp-auth-token.png" alt="인증 토큰을 사용하는 커스텀 MCP 서버" />
+</Frame>
+
+| 필드 | 필수 | 설명 |
+|------|------|------|
+| **Header Name** | 예 | 토큰을 전달하는 HTTP 헤더 이름 (예: `X-API-Key`, `Authorization`). |
+| **Value** | 예 | API 키 또는 Bearer 토큰. |
+| **Add to** | 아니오 | 자격 증명을 첨부할 위치 — **Header** (기본값) 또는 **Query parameter**. |
+
+<Tip>
+서버가 `Authorization` 헤더에 `Bearer` 토큰을 예상하는 경우, Header Name을 `Authorization`으로, Value를 `Bearer <토큰>`으로 설정하세요.
+</Tip>
+
+### OAuth 2.0
+
+OAuth 2.0 인증이 필요한 MCP 서버에 이 방법을 사용합니다. CrewAI가 토큰 갱신을 포함한 전체 OAuth 흐름을 처리합니다.
+
+<Frame>
+    <img src="/images/enterprise/custom-mcp-oauth.png" alt="OAuth 2.0을 사용하는 커스텀 MCP 서버" />
+</Frame>
+
+| 필드 | 필수 | 설명 |
+|------|------|------|
+| **Redirect URI** | — | 자동으로 채워지며 읽기 전용입니다. 이 URI를 복사하여 OAuth 제공자에 승인된 리디렉션 URI로 등록하세요. |
+| **Authorization Endpoint** | 예 | 사용자가 접근을 승인하기 위해 이동하는 URL (예: `https://auth.example.com/oauth/authorize`). |
+| **Token Endpoint** | 예 | 인증 코드를 액세스 토큰으로 교환하는 데 사용되는 URL (예: `https://auth.example.com/oauth/token`). |
+| **Client ID** | 예 | OAuth 제공자가 발급한 클라이언트 ID. |
+| **Client Secret** | 아니오 | OAuth 클라이언트 시크릿. PKCE를 사용하는 공개 클라이언트에는 필요하지 않습니다. |
+| **Scopes** | 아니오 | 요청할 스코프의 공백으로 구분된 목록 (예: `read write`). |
+| **Token Auth Method** | 아니오 | 토큰 교환 시 클라이언트 자격 증명을 보내는 방법 — **Standard (POST body)** 또는 **Basic Auth (header)**. 기본값은 Standard입니다. |
+| **PKCE Supported** | 아니오 | OAuth 제공자가 Proof Key for Code Exchange를 지원하는 경우 활성화합니다. 보안 강화를 위해 권장됩니다. |
+
+<Info>
+**Discover OAuth Config**: OAuth 제공자가 OpenID Connect Discovery를 지원하는 경우, **Discover OAuth Config** 링크를 클릭하여 제공자의 `/.well-known/openid-configuration` URL에서 인증 및 토큰 엔드포인트를 자동으로 채울 수 있습니다.
+</Info>
+
+#### OAuth 2.0 단계별 설정
+
+<Steps>
+    <Step title="리디렉션 URI 등록">
+        양식에 표시된 **Redirect URI**를 복사하여 OAuth 제공자의 애플리케이션 설정에서 승인된 리디렉션 URI로 추가합니다.
+    </Step>
+
+    <Step title="엔드포인트 및 자격 증명 입력">
+        **Authorization Endpoint**, **Token Endpoint**, **Client ID**를 입력하고, 선택적으로 **Client Secret**과 **Scopes**를 입력합니다.
+    </Step>
+
+    <Step title="토큰 교환 방법 구성">
+        적절한 **Token Auth Method**를 선택합니다. 대부분의 제공자는 기본값인 **Standard (POST body)**를 사용합니다. 일부 오래된 제공자는 **Basic Auth (header)**를 요구합니다.
+    </Step>
+
+    <Step title="PKCE 활성화 (권장)">
+        제공자가 지원하는 경우 **PKCE Supported**를 체크합니다. PKCE는 인증 코드 흐름에 추가 보안 계층을 제공하며 모든 새 통합에 권장됩니다.
+    </Step>
+
+    <Step title="생성 및 인증">
+        **Create MCP Server**를 클릭합니다. OAuth 제공자로 리디렉션되어 접근을 인증합니다. 인증 완료 후 CrewAI가 토큰을 저장하고 필요에 따라 자동으로 갱신합니다.
+    </Step>
+</Steps>
+
+## 커스텀 MCP 서버 사용하기
+
+연결이 완료되면 커스텀 MCP 서버의 도구가 **Tools & Integrations** 페이지에서 기본 제공 연결과 함께 표시됩니다. 다음을 수행할 수 있습니다:
+
+- 다른 CrewAI 도구와 마찬가지로 crew의 **에이전트에 도구를 할당**합니다.
+- **가시성을 관리**하여 어떤 팀원이 서버를 사용할 수 있는지 제어합니다.
+- Connections 목록에서 언제든지 연결을 **편집하거나 제거**합니다.
+
+<Warning>
+MCP 서버에 접근할 수 없거나 자격 증명이 만료되면 해당 서버를 사용하는 도구 호출이 실패합니다. 서버 URL이 안정적이고 자격 증명이 최신 상태인지 확인하세요.
+</Warning>
+
+<Card title="도움이 필요하신가요?" icon="headset" href="mailto:support@crewai.com">
+  커스텀 MCP 서버 구성 또는 문제 해결에 대한 도움이 필요하면 지원팀에 문의하세요.
+</Card>
@@ -9,10 +9,7 @@ mode: "wide"

 Tool Repository는 CrewAI 도구를 위한 패키지 관리자입니다. 사용자는 CrewAI crew와 flow에 통합되는 도구를 게시, 설치 및 관리할 수 있습니다.

-도구는 다음과 같이 분류됩니다:
-
- **비공개**: 조직 내에서만 접근할 수 있습니다(기본값)
- **공개**: `--public` 플래그로 게시하면 모든 CrewAI 사용자가 접근할 수 있습니다
+모든 도구는 기본적으로 비공개이며 조직 내에서만 접근할 수 있습니다.

 이 저장소는 버전 관리 시스템이 아닙니다. 코드 변경 사항을 추적하고 협업을 활성화하려면 Git을 사용하십시오.

@@ -60,12 +57,6 @@ git commit -m "Initial version"
 crewai tool publish
 ```

-기본적으로 도구는 비공개로 게시됩니다. 도구를 공개로 설정하려면:
-
-```bash
-crewai tool publish --public
-```
-
 도구 빌드에 대한 자세한 내용은 [나만의 도구 만들기](/ko/concepts/tools#creating-your-own-tools)를 참고하세요.

 ## 도구 업데이트
@@ -4,6 +4,47 @@ description: "Atualizações de produto, melhorias e correções do CrewAI"
 icon: "clock"
 mode: "wide"
 ---
+<Update label="18 mar 2026">
+  ## v1.11.0
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.11.0)
+
+  ## O que Mudou
+
+  ### Documentação
+  - Atualizar changelog e versão para v1.11.0rc2
+
+  ## Contribuidores
+
+  @greysonlalonde
+
+</Update>
+
+<Update label="17 mar 2026">
+  ## v1.11.0rc2
+
+  [Ver release no GitHub](https://github.com/crewAIInc/crewAI/releases/tag/1.11.0rc2)
+
+  ## O que Mudou
+
+  ### Correções de Bugs
+  - Aprimorar o manuseio e a serialização das respostas do LLM.
+  - Atualizar dependências transitivas vulneráveis (authlib, PyJWT, snowflake-connector-python).
+  - Substituir `os.system` por `subprocess.run` na instalação do pip em modo inseguro.
+
+  ### Documentação
+  - Atualizar a página da Ferramenta de Pesquisa Exa com nomes, descrições e opções de configuração aprimoradas.
+  - Adicionar Servidores MCP Personalizados no Guia de Como Fazer.
+  - Atualizar a documentação dos coletores OTEL.
+  - Atualizar a documentação do MCP.
+  - Atualizar o changelog e a versão para v1.11.0rc1.
+
+  ## Contributors
+
+  @10ishq, @greysonlalonde, @joaomdmoura, @lucasgomide, @mattatcha, @theCyberTech, @vinibrsl
+
+</Update>
+
 <Update label="15 mar 2026">
  ## v1.11.0rc1

@@ -0,0 +1,39 @@
+---
+title: "Exportação OpenTelemetry"
+description: "Exporte traces e logs das suas implantações CrewAI AMP para seu próprio coletor OpenTelemetry"
+icon: "magnifying-glass-chart"
+mode: "wide"
+---
+
+O CrewAI AMP pode exportar **traces** e **logs** do OpenTelemetry das suas implantações diretamente para seu próprio coletor. Isso permite que você monitore o desempenho dos agentes, rastreie chamadas de LLM e depure problemas usando sua stack de observabilidade existente.
+
+Os dados de telemetria seguem as [convenções semânticas GenAI do OpenTelemetry](https://opentelemetry.io/docs/specs/semconv/gen-ai/) além de atributos adicionais específicos do CrewAI.
+
+## Pré-requisitos
+
+<CardGroup cols={2}>
+  <Card title="Conta CrewAI AMP" icon="users">
+    Sua organização deve ter uma conta CrewAI AMP ativa.
+  </Card>
+  <Card title="Coletor OpenTelemetry" icon="server">
+    Você precisa de um endpoint de coletor compatível com OpenTelemetry (por exemplo, seu próprio OTel Collector, Datadog, Grafana ou qualquer backend compatível com OTLP).
+  </Card>
+</CardGroup>
+
+## Configurando um coletor
+
+1. No CrewAI AMP, vá para **Settings** > **OpenTelemetry Collectors**.
+2. Clique em **Add Collector**.
+3. Selecione um tipo de integração — **OpenTelemetry Traces** ou **OpenTelemetry Logs**.
+4. Configure a conexão:
+   - **Endpoint** — O endpoint OTLP do seu coletor (por exemplo, `https://otel-collector.example.com:4317`).
+   - **Service Name** — Um nome para identificar este serviço na sua plataforma de observabilidade.
+   - **Custom Headers** *(opcional)* — Adicione headers de autenticação ou roteamento como pares chave-valor.
+   - **Certificate** *(opcional)* — Forneça um certificado TLS se o seu coletor exigir um.
+5. Clique em **Save**.
+
+<Frame>![Configuração do Coletor OpenTelemetry](/images/crewai-otel-collector-config.png)</Frame>
+
+<Tip>
+  Você pode adicionar múltiplos coletores — por exemplo, um para traces e outro para logs, ou enviar para diferentes backends para diferentes propósitos.
+</Tip>
@@ -0,0 +1,136 @@
+---
+title: "Servidores MCP Personalizados"
+description: "Conecte seus próprios servidores MCP ao CrewAI AMP com acesso público, autenticação por token ou OAuth 2.0"
+icon: "plug"
+mode: "wide"
+---
+
+O CrewAI AMP suporta a conexão com qualquer servidor MCP que implemente o [Model Context Protocol](https://modelcontextprotocol.io/). Você pode conectar servidores públicos que não exigem autenticação, servidores protegidos por chave de API ou token bearer, e servidores que utilizam OAuth 2.0 para acesso delegado seguro.
+
+## Pré-requisitos
+
+<CardGroup cols={2}>
+  <Card title="Conta CrewAI AMP" icon="user">
+    Você precisa de uma conta ativa no [CrewAI AMP](https://app.crewai.com).
+  </Card>
+  <Card title="URL do Servidor MCP" icon="link">
+    A URL do servidor MCP que você deseja conectar. O servidor deve ser acessível pela internet e suportar transporte Streamable HTTP.
+  </Card>
+</CardGroup>
+
+## Adicionando um Servidor MCP Personalizado
+
+<Steps>
+    <Step title="Acesse Tools & Integrations">
+        Navegue até **Tools & Integrations** no menu lateral esquerdo do CrewAI AMP e selecione a aba **Connections**.
+    </Step>
+
+    <Step title="Inicie a adição de um Servidor MCP Personalizado">
+        Clique no botão **Add Custom MCP Server**. Um diálogo aparecerá com o formulário de configuração.
+    </Step>
+
+    <Step title="Preencha as informações básicas">
+        - **Name** (obrigatório): Um nome descritivo para seu servidor MCP (ex.: "Meu Servidor de Ferramentas Internas").
+        - **Description**: Um resumo opcional do que este servidor MCP fornece.
+        - **Server URL** (obrigatório): A URL completa do endpoint do seu servidor MCP (ex.: `https://my-server.example.com/mcp`).
+    </Step>
+
+    <Step title="Escolha um método de autenticação">
+        Selecione um dos três métodos de autenticação disponíveis com base em como seu servidor MCP está protegido. Veja as seções abaixo para detalhes sobre cada método.
+    </Step>
+
+    <Step title="Adicione headers personalizados (opcional)">
+        Se seu servidor MCP requer headers adicionais em cada requisição (ex.: identificadores de tenant ou headers de roteamento), clique em **+ Add Header** e forneça o nome e valor do header. Você pode adicionar múltiplos headers personalizados.
+    </Step>
+
+    <Step title="Crie a conexão">
+        Clique em **Create MCP Server** para salvar a conexão. Seu servidor MCP personalizado aparecerá na lista de Connections e suas ferramentas estarão disponíveis para uso nas suas crews.
+    </Step>
+</Steps>
+
+## Métodos de Autenticação
+
+### Sem Autenticação
+
+Escolha esta opção quando seu servidor MCP é publicamente acessível e não requer nenhuma credencial. Isso é comum para servidores open-source ou servidores internos rodando atrás de uma VPN.
+
+### Token de Autenticação
+
+Use este método quando seu servidor MCP é protegido por uma chave de API ou token bearer.
+
+<Frame>
+    <img src="/images/enterprise/custom-mcp-auth-token.png" alt="Servidor MCP Personalizado com Token de Autenticação" />
+</Frame>
+
+| Campo | Obrigatório | Descrição |
+|-------|-------------|-----------|
+| **Header Name** | Sim | O nome do header HTTP que carrega o token (ex.: `X-API-Key`, `Authorization`). |
+| **Value** | Sim | Sua chave de API ou token bearer. |
+| **Add to** | Não | Onde anexar a credencial — **Header** (padrão) ou **Query parameter**. |
+
+<Tip>
+Se seu servidor espera um token `Bearer` no header `Authorization`, defina o Header Name como `Authorization` e o Value como `Bearer <seu-token>`.
+</Tip>
+
+### OAuth 2.0
+
+Use este método para servidores MCP que requerem autorização OAuth 2.0. O CrewAI gerenciará todo o fluxo OAuth, incluindo a renovação de tokens.
+
+<Frame>
+    <img src="/images/enterprise/custom-mcp-oauth.png" alt="Servidor MCP Personalizado com OAuth 2.0" />
+</Frame>
+
+| Campo | Obrigatório | Descrição |
+|-------|-------------|-----------|
+| **Redirect URI** | — | Preenchido automaticamente e somente leitura. Copie esta URI e registre-a como URI de redirecionamento autorizada no seu provedor OAuth. |
+| **Authorization Endpoint** | Sim | A URL para onde os usuários são enviados para autorizar o acesso (ex.: `https://auth.example.com/oauth/authorize`). |
+| **Token Endpoint** | Sim | A URL usada para trocar o código de autorização por um token de acesso (ex.: `https://auth.example.com/oauth/token`). |
+| **Client ID** | Sim | O Client ID OAuth emitido pelo seu provedor. |
+| **Client Secret** | Não | O Client Secret OAuth. Não é necessário para clientes públicos usando PKCE. |
+| **Scopes** | Não | Lista de escopos separados por espaço a solicitar (ex.: `read write`). |
+| **Token Auth Method** | Não | Como as credenciais do cliente são enviadas ao trocar tokens — **Standard (POST body)** ou **Basic Auth (header)**. Padrão é Standard. |
+| **PKCE Supported** | Não | Ative se seu provedor OAuth suporta Proof Key for Code Exchange. Recomendado para maior segurança. |
+
+<Info>
+**Discover OAuth Config**: Se seu provedor OAuth suporta OpenID Connect Discovery, clique no link **Discover OAuth Config** para preencher automaticamente os endpoints de autorização e token a partir da URL `/.well-known/openid-configuration` do provedor.
+</Info>
+
+#### Configurando OAuth 2.0 Passo a Passo
+
+<Steps>
+    <Step title="Registre a URI de redirecionamento">
+        Copie a **Redirect URI** exibida no formulário e adicione-a como URI de redirecionamento autorizada nas configurações do seu provedor OAuth.
+    </Step>
+
+    <Step title="Insira os endpoints e credenciais">
+        Preencha o **Authorization Endpoint**, **Token Endpoint**, **Client ID** e, opcionalmente, o **Client Secret** e **Scopes**.
+    </Step>
+
+    <Step title="Configure o método de troca de tokens">
+        Selecione o **Token Auth Method** apropriado. A maioria dos provedores usa o padrão **Standard (POST body)**. Alguns provedores mais antigos requerem **Basic Auth (header)**.
+    </Step>
+
+    <Step title="Ative o PKCE (recomendado)">
+        Marque **PKCE Supported** se seu provedor suporta. O PKCE adiciona uma camada extra de segurança ao fluxo de código de autorização e é recomendado para todas as novas integrações.
+    </Step>
+
+    <Step title="Crie e autorize">
+        Clique em **Create MCP Server**. Você será redirecionado ao seu provedor OAuth para autorizar o acesso. Uma vez autorizado, o CrewAI armazenará os tokens e os renovará automaticamente conforme necessário.
+    </Step>
+</Steps>
+
+## Usando Seu Servidor MCP Personalizado
+
+Uma vez conectado, as ferramentas do seu servidor MCP personalizado aparecem junto com as conexões integradas na página **Tools & Integrations**. Você pode:
+
+- **Atribuir ferramentas a agentes** nas suas crews, assim como qualquer outra ferramenta CrewAI.
+- **Gerenciar visibilidade** para controlar quais membros da equipe podem usar o servidor.
+- **Editar ou remover** a conexão a qualquer momento na lista de Connections.
+
+<Warning>
+Se seu servidor MCP ficar inacessível ou as credenciais expirarem, as chamadas de ferramentas usando esse servidor falharão. Certifique-se de que a URL do servidor seja estável e as credenciais estejam atualizadas.
+</Warning>
+
+<Card title="Precisa de Ajuda?" icon="headset" href="mailto:support@crewai.com">
+  Entre em contato com nossa equipe de suporte para assistência com configuração ou resolução de problemas de servidores MCP personalizados.
+</Card>
@@ -9,10 +9,7 @@ mode: "wide"

 O Repositório de Ferramentas é um gerenciador de pacotes para ferramentas da CrewAI. Ele permite que usuários publiquem, instalem e gerenciem ferramentas que se integram com crews e flows da CrewAI.

-As ferramentas podem ser:
-
- **Privadas**: acessíveis apenas dentro da sua organização (padrão)
- **Públicas**: acessíveis a todos os usuários CrewAI se publicadas com a flag `--public`
+Todas as ferramentas são privadas por padrão e acessíveis apenas dentro da sua organização.

 O repositório não é um sistema de controle de versões. Use Git para rastrear mudanças no código e permitir colaboração.

@@ -60,12 +57,6 @@ Para publicar a ferramenta:
 crewai tool publish
 ```

-Por padrão, as ferramentas são publicadas como privadas. Para tornar uma ferramenta pública:
-
-```bash
-crewai tool publish --public
-```
-
 Para mais detalhes sobre como construir ferramentas, acesse [Criando suas próprias ferramentas](/pt-BR/concepts/tools#creating-your-own-tools).

 ## Atualizando ferramentas
@@ -152,4 +152,4 @@ __all__ = [
    "wrap_file_source",
 ]

-__version__ = "1.11.0rc1"
+__version__ = "1.11.0"
@@ -11,7 +11,7 @@ dependencies = [
    "pytube~=15.0.0",
    "requests~=2.32.5",
    "docker~=7.1.0",
-    "crewai==1.11.0rc1",
+    "crewai==1.11.0",
    "tiktoken~=0.8.0",
    "beautifulsoup4~=4.13.4",
    "python-docx~=1.2.0",
@@ -309,4 +309,4 @@ __all__ = [
    "ZapierActionTools",
 ]

-__version__ = "1.11.0rc1"
+__version__ = "1.11.0"
@@ -53,7 +53,7 @@ Repository = "https://github.com/crewAIInc/crewAI"

 [project.optional-dependencies]
 tools = [
-    "crewai-tools==1.11.0rc1",
+    "crewai-tools==1.11.0",
 ]
 embeddings = [
    "tiktoken~=0.8.0"
@@ -42,7 +42,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:

 _suppress_pydantic_deprecation_warnings()

-__version__ = "1.11.0rc1"
+__version__ = "1.11.0"
 _telemetry_submitted = False


@@ -452,12 +452,10 @@ def tool_install(handle: str):
    default=False,
    help="Bypasses Git remote validations",
 )
-@click.option("--public", "is_public", flag_value=True, default=False)
-@click.option("--private", "is_public", flag_value=False)
-def tool_publish(is_public: bool, force: bool):
+def tool_publish(force: bool):
    tool_cmd = ToolCommand()
    tool_cmd.login()
-    tool_cmd.publish(is_public, force)
+    tool_cmd.publish(force)


@crewai.group()
@@ -68,7 +68,6 @@ class PlusAPI:
    def publish_tool(
        self,
        handle: str,
-        is_public: bool,
        version: str,
        description: str | None,
        encoded_file: str,
@@ -76,7 +75,6 @@ class PlusAPI:
    ) -> httpx.Response:
        params = {
            "handle": handle,
-            "public": is_public,
            "version": version,
            "file": encoded_file,
            "description": description,
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.11.0rc1"
+    "crewai[tools]==1.11.0"
 ]

 [project.scripts]
@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.11.0rc1"
+    "crewai[tools]==1.11.0"
 ]

 [project.scripts]
@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<3.14"
 dependencies = [
-    "crewai[tools]==1.11.0rc1"
+    "crewai[tools]==1.11.0"
 ]

 [tool.crewai]
@@ -73,7 +73,7 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
        finally:
            os.chdir(old_directory)

-    def publish(self, is_public: bool, force: bool = False) -> None:
+    def publish(self, force: bool = False) -> None:
        if not git.Repository().is_synced() and not force:
            console.print(
                "[bold red]Failed to publish tool.[/bold red]\n"
@@ -129,7 +129,6 @@ class ToolCommand(BaseCommand, PlusAPIMixin):
        console.print("[bold blue]Publishing tool to repository...[/bold blue]")
        publish_response = self.plus_api_client.publish_tool(
            handle=project_name,
-            is_public=is_public,
            version=project_version,
            description=project_description,
            encoded_file=f"data:application/x-gzip;base64,{encoded_tarball}",
@@ -3086,25 +3086,35 @@ class Flow(Generic[T], metaclass=FlowMeta):
            logger.warning(
                f"Structured output failed, falling back to simple prompting: {e}"
            )
-            response = llm_instance.call(messages=prompt)
-            response_clean = str(response).strip()
+            try:
+                response = llm_instance.call(
+                    messages=[{"role": "user", "content": prompt}],
+                )
+                response_clean = str(response).strip()

-            # Exact match (case-insensitive)
-            for outcome in outcomes:
-                if outcome.lower() == response_clean.lower():
-                    return outcome
+                # Exact match (case-insensitive)
+                for outcome in outcomes:
+                    if outcome.lower() == response_clean.lower():
+                        return outcome

-            # Partial match
-            for outcome in outcomes:
-                if outcome.lower() in response_clean.lower():
-                    return outcome
+                # Partial match
+                for outcome in outcomes:
+                    if outcome.lower() in response_clean.lower():
+                        return outcome

-            # Fallback to first outcome
-            logger.warning(
-                f"Could not match LLM response '{response_clean}' to outcomes {list(outcomes)}. "
-                f"Falling back to first outcome: {outcomes[0]}"
-            )
-            return outcomes[0]
+                # Fallback to first outcome
+                logger.warning(
+                    f"Could not match LLM response '{response_clean}' to outcomes {list(outcomes)}. "
+                    f"Falling back to first outcome: {outcomes[0]}"
+                )
+                return outcomes[0]
+
+            except Exception as fallback_err:
+                logger.warning(
+                    f"Simple prompting also failed: {fallback_err}. "
+                    f"Falling back to first outcome: {outcomes[0]}"
+                )
+                return outcomes[0]

    def _log_flow_event(
        self,
@@ -76,6 +76,24 @@ if TYPE_CHECKING:
 F = TypeVar("F", bound=Callable[..., Any])


+def _serialize_llm_for_context(llm: Any) -> str | None:
+    """Serialize a BaseLLM object to a model string with provider prefix.
+
+    When persisting the LLM for HITL resume, we need to store enough info
+    to reconstruct a working LLM on the resume worker. Just storing the bare
+    model name (e.g. "gemini-3-flash-preview") causes provider inference to
+    fail — it defaults to OpenAI. Including the provider prefix (e.g.
+    "gemini/gemini-3-flash-preview") allows LLM() to correctly route.
+    """
+    model = getattr(llm, "model", None)
+    if not model:
+        return None
+    provider = getattr(llm, "provider", None)
+    if provider and "/" not in model:
+        return f"{provider}/{model}"
+    return model
+
+
@dataclass
 class HumanFeedbackResult:
    """Result from a @human_feedback decorated method.
@@ -412,7 +430,7 @@ def human_feedback(
                emit=list(emit) if emit else None,
                default_outcome=default_outcome,
                metadata=metadata or {},
-                llm=llm if isinstance(llm, str) else getattr(llm, "model", None),
+                llm=llm if isinstance(llm, str) else _serialize_llm_for_context(llm),
            )

            # Determine effective provider:
@@ -240,6 +240,7 @@ ANTHROPIC_MODELS: list[AnthropicModels] = [

 GeminiModels: TypeAlias = Literal[
    "gemini-3-pro-preview",
+    "gemini-3-flash-preview",
    "gemini-2.5-pro",
    "gemini-2.5-pro-preview-03-25",
    "gemini-2.5-pro-preview-05-06",
@@ -294,6 +295,7 @@ GeminiModels: TypeAlias = Literal[
 ]
 GEMINI_MODELS: list[GeminiModels] = [
    "gemini-3-pro-preview",
+    "gemini-3-flash-preview",
    "gemini-2.5-pro",
    "gemini-2.5-pro-preview-03-25",
    "gemini-2.5-pro-preview-05-06",
@@ -120,18 +120,16 @@ class TestPlusAPI(unittest.TestCase):
        mock_response = MagicMock()
        mock_make_request.return_value = mock_response
        handle = "test_tool_handle"
-        public = True
        version = "1.0.0"
        description = "Test tool description"
        encoded_file = "encoded_test_file"

        response = self.api.publish_tool(
-            handle, public, version, description, encoded_file
+            handle, version, description, encoded_file
        )

        params = {
            "handle": handle,
-            "public": public,
            "version": version,
            "file": encoded_file,
            "description": description,
@@ -157,18 +155,16 @@ class TestPlusAPI(unittest.TestCase):
        mock_client_class.return_value.__enter__.return_value = mock_client_instance

        handle = "test_tool_handle"
-        public = True
        version = "1.0.0"
        description = "Test tool description"
        encoded_file = "encoded_test_file"

        response = self.api.publish_tool(
-            handle, public, version, description, encoded_file
+            handle, version, description, encoded_file
        )

        expected_params = {
            "handle": handle,
-            "public": public,
            "version": version,
            "file": encoded_file,
            "description": description,
@@ -185,18 +181,16 @@ class TestPlusAPI(unittest.TestCase):
        mock_response = MagicMock()
        mock_make_request.return_value = mock_response
        handle = "test_tool_handle"
-        public = False
        version = "2.0.0"
        description = None
        encoded_file = "encoded_test_file"

        response = self.api.publish_tool(
-            handle, public, version, description, encoded_file
+            handle, version, description, encoded_file
        )

        params = {
            "handle": handle,
-            "public": public,
            "version": version,
            "file": encoded_file,
            "description": description,
@@ -163,7 +163,7 @@ def test_install_api_error(mock_get, capsys, tool_command):
@patch("crewai.cli.tools.main.git.Repository.is_synced", return_value=False)
 def test_publish_when_not_in_sync(mock_is_synced, capsys, tool_command):
    with raises(SystemExit):
-        tool_command.publish(is_public=True)
+        tool_command.publish()

    output = capsys.readouterr().out
    assert "Local changes need to be resolved before publishing" in output
@@ -204,7 +204,7 @@ def test_publish_when_not_in_sync_and_force(
    mock_publish_response.json.return_value = {"handle": "sample-tool"}
    mock_publish.return_value = mock_publish_response

-    tool_command.publish(is_public=True, force=True)
+    tool_command.publish(force=True)

    mock_get_project_name.assert_called_with(require=True)
    mock_get_project_version.assert_called_with(require=True)
@@ -217,7 +217,6 @@ def test_publish_when_not_in_sync_and_force(
    mock_open.assert_called_with(unittest.mock.ANY, "rb")
    mock_publish.assert_called_with(
        handle="sample-tool",
-        is_public=True,
        version="1.0.0",
        description="A sample tool",
        encoded_file=unittest.mock.ANY,
@@ -259,7 +258,7 @@ def test_publish_success(
    mock_publish_response.json.return_value = {"handle": "sample-tool"}
    mock_publish.return_value = mock_publish_response

-    tool_command.publish(is_public=True)
+    tool_command.publish()

    mock_get_project_name.assert_called_with(require=True)
    mock_get_project_version.assert_called_with(require=True)
@@ -272,7 +271,6 @@ def test_publish_success(
    mock_open.assert_called_with(unittest.mock.ANY, "rb")
    mock_publish.assert_called_with(
        handle="sample-tool",
-        is_public=True,
        version="1.0.0",
        description="A sample tool",
        encoded_file=unittest.mock.ANY,
@@ -313,7 +311,7 @@ def test_publish_failure(
    mock_publish.return_value = mock_publish_response

    with raises(SystemExit):
-        tool_command.publish(is_public=True)
+        tool_command.publish()
    output = capsys.readouterr().out
    assert "Failed to complete operation" in output
    assert "Name is already taken" in output
@@ -355,7 +353,7 @@ def test_publish_api_error(
    mock_publish.return_value = mock_response

    with raises(SystemExit):
-        tool_command.publish(is_public=True)
+        tool_command.publish()
    output = capsys.readouterr().out
    assert "Request to Enterprise API failed" in output

@@ -989,8 +989,10 @@ class TestLLMObjectPreservedInContext:
            persistence = SQLiteFlowPersistence(db_path)

            # Create a mock BaseLLM object (not a string)
+            # Simulates LLM(model="gemini-2.0-flash", provider="gemini")
            mock_llm_obj = MagicMock()
-            mock_llm_obj.model = "gemini/gemini-2.0-flash"
+            mock_llm_obj.model = "gemini-2.0-flash"
+            mock_llm_obj.provider = "gemini"

            class PausingProvider:
                def __init__(self, persistence: SQLiteFlowPersistence):
@@ -1086,11 +1088,36 @@ class TestLLMObjectPreservedInContext:

    def test_none_llm_when_no_model_attr(self) -> None:
        """Test that llm is None when object has no model attribute."""
-        mock_obj = MagicMock(spec=[])  # No attributes
+        from crewai.flow.human_feedback import _serialize_llm_for_context

-        # Simulate what the decorator does
-        llm_value = mock_obj if isinstance(mock_obj, str) else getattr(mock_obj, "model", None)
-        assert llm_value is None
+        mock_obj = MagicMock(spec=[])  # No attributes
+        assert _serialize_llm_for_context(mock_obj) is None
+
+    def test_provider_prefix_added_to_bare_model(self) -> None:
+        """Test that provider prefix is added when model has no slash."""
+        from crewai.flow.human_feedback import _serialize_llm_for_context
+
+        mock_obj = MagicMock()
+        mock_obj.model = "gemini-3-flash-preview"
+        mock_obj.provider = "gemini"
+        assert _serialize_llm_for_context(mock_obj) == "gemini/gemini-3-flash-preview"
+
+    def test_provider_prefix_not_doubled_when_already_present(self) -> None:
+        """Test that provider prefix is not added when model already has a slash."""
+        from crewai.flow.human_feedback import _serialize_llm_for_context
+
+        mock_obj = MagicMock()
+        mock_obj.model = "gemini/gemini-2.0-flash"
+        mock_obj.provider = "gemini"
+        assert _serialize_llm_for_context(mock_obj) == "gemini/gemini-2.0-flash"
+
+    def test_no_provider_attr_falls_back_to_bare_model(self) -> None:
+        """Test that bare model is used when no provider attribute exists."""
+        from crewai.flow.human_feedback import _serialize_llm_for_context
+
+        mock_obj = MagicMock(spec=[])
+        mock_obj.model = "gpt-4o-mini"
+        assert _serialize_llm_for_context(mock_obj) == "gpt-4o-mini"


 class TestAsyncHumanFeedbackEdgeCases:
@@ -400,6 +400,45 @@ class TestCollapseToOutcome:

        assert result == "approved"  # First in list

+    def test_both_llm_calls_fail_returns_first_outcome(self):
+        """When both structured and simple prompting fail, return outcomes[0]."""
+        flow = Flow()
+
+        with patch("crewai.llm.LLM") as MockLLM:
+            mock_llm = MagicMock()
+            # Both calls raise — simulates wrong provider / auth failure
+            mock_llm.call.side_effect = RuntimeError("Model not found")
+            MockLLM.return_value = mock_llm
+
+            result = flow._collapse_to_outcome(
+                feedback="looks great, approve it",
+                outcomes=["needs_changes", "approved"],
+                llm="gemini-3-flash-preview",
+            )
+
+        assert result == "needs_changes"  # First in list (safe fallback)
+
+    def test_structured_fails_but_simple_succeeds(self):
+        """When structured output fails but simple prompting works, use that."""
+        flow = Flow()
+
+        with patch("crewai.llm.LLM") as MockLLM:
+            mock_llm = MagicMock()
+            # First call (structured) fails, second call (simple) succeeds
+            mock_llm.call.side_effect = [
+                RuntimeError("Function calling not supported"),
+                "approved",
+            ]
+            MockLLM.return_value = mock_llm
+
+            result = flow._collapse_to_outcome(
+                feedback="looks great",
+                outcomes=["needs_changes", "approved"],
+                llm="gpt-4o-mini",
+            )
+
+        assert result == "approved"
+

 # -- HITL Learning tests --

@@ -1,3 +1,3 @@
 """CrewAI development tools."""

-__version__ = "1.11.0rc1"
+__version__ = "1.11.0"
@@ -408,14 +408,14 @@ wheels = [

 [[package]]
 name = "authlib"
-version = "1.6.7"
+version = "1.6.9"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "cryptography" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/49/dc/ed1681bf1339dd6ea1ce56136bad4baabc6f7ad466e375810702b0237047/authlib-1.6.7.tar.gz", hash = "sha256:dbf10100011d1e1b34048c9d120e83f13b35d69a826ae762b93d2fb5aafc337b", size = 164950, upload-time = "2026-02-06T14:04:14.171Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/af/98/00d3dd826d46959ad8e32af2dbb2398868fd9fd0683c26e56d0789bd0e68/authlib-1.6.9.tar.gz", hash = "sha256:d8f2421e7e5980cc1ddb4e32d3f5fa659cfaf60d8eaf3281ebed192e4ab74f04", size = 165134, upload-time = "2026-03-02T07:44:01.998Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/f8/00/3ed12264094ec91f534fae429945efbaa9f8c666f3aa7061cc3b2a26a0cd/authlib-1.6.7-py2.py3-none-any.whl", hash = "sha256:c637340d9a02789d2efa1d003a7437d10d3e565237bcb5fcbc6c134c7b95bab0", size = 244115, upload-time = "2026-02-06T14:04:12.141Z" },
+    { url = "https://files.pythonhosted.org/packages/53/23/b65f568ed0c22f1efacb744d2db1a33c8068f384b8c9b482b52ebdbc3ef6/authlib-1.6.9-py2.py3-none-any.whl", hash = "sha256:f08b4c14e08f0861dc18a32357b33fbcfd2ea86cfe3fe149484b4d764c4a0ac3", size = 244197, upload-time = "2026-03-02T07:44:00.307Z" },
 ]

 [[package]]
@@ -5940,11 +5940,14 @@ wheels = [

 [[package]]
 name = "pyjwt"
-version = "2.11.0"
+version = "2.12.1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/5c/5a/b46fa56bf322901eee5b0454a34343cdbdae202cd421775a8ee4e42fd519/pyjwt-2.11.0.tar.gz", hash = "sha256:35f95c1f0fbe5d5ba6e43f00271c275f7a1a4db1dab27bf708073b75318ea623", size = 98019, upload-time = "2026-01-30T19:59:55.694Z" }
+dependencies = [
+    { name = "typing-extensions", marker = "python_full_version < '3.11'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/c2/27/a3b6e5bf6ff856d2509292e95c8f57f0df7017cf5394921fc4e4ef40308a/pyjwt-2.12.1.tar.gz", hash = "sha256:c74a7a2adf861c04d002db713dd85f84beb242228e671280bf709d765b03672b", size = 102564, upload-time = "2026-03-13T19:27:37.25Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/6f/01/c26ce75ba460d5cd503da9e13b21a33804d38c2165dec7b716d06b13010c/pyjwt-2.11.0-py3-none-any.whl", hash = "sha256:94a6bde30eb5c8e04fee991062b534071fd1439ef58d2adc9ccb823e7bcd0469", size = 28224, upload-time = "2026-01-30T19:59:54.539Z" },
+    { url = "https://files.pythonhosted.org/packages/e5/7a/8dd906bd22e79e47397a61742927f6747fe93242ef86645ee9092e610244/pyjwt-2.12.1-py3-none-any.whl", hash = "sha256:28ca37c070cad8ba8cd9790cd940535d40274d22f80ab87f3ac6a713e6e8454c", size = 29726, upload-time = "2026-03-13T19:27:35.677Z" },
 ]

 [package.optional-dependencies]
@@ -7307,7 +7310,7 @@ wheels = [

 [[package]]
 name = "snowflake-connector-python"
-version = "4.2.0"
+version = "4.3.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "asn1crypto" },
@@ -7329,28 +7332,28 @@ dependencies = [
    { name = "typing-extensions" },
    { name = "urllib3" },
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Author	SHA1	Message	Date
Heitor Sammuel Carvalho	a60aa3daca	feat: remove --public/--private flags from tool publish command All tools are now private to the organization by default. The --public and --private CLI flags have been removed along with the is_public parameter throughout the stack. Docs updated across EN, PT-BR, and KO.	2026-03-18 13:28:59 -03:00
Greyson LaLonde	116182f708	docs: update changelog and version for v1.11.0	2026-03-18 09:38:38 -04:00
Greyson LaLonde	9eed13b8a2	feat: bump versions to 1.11.0	2026-03-18 09:30:05 -04:00
Greyson LaLonde	50b2c7d072	docs: update changelog and version for v1.11.0rc2 CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details Nightly Canary Release / Check for new commits (push) Has been cancelled Details Nightly Canary Release / Build nightly packages (push) Has been cancelled Details Nightly Canary Release / Publish nightly to PyPI (push) Has been cancelled Details Mark stale issues and pull requests / stale (push) Has been cancelled Details	2026-03-17 17:07:26 -04:00
Greyson LaLonde	e9ba4932a0	feat: bump versions to 1.11.0rc2	2026-03-17 16:58:59 -04:00
Tanishq Tanishq Jaiswal João Moura	0b07b4c45f	docs: update Exa Search Tool page with improved naming, description, and configuration options (#4800 ) CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details * docs: update Exa Search Tool page with improved naming, description, and configuration options Co-Authored-By: Tanishq Jaiswal <tanishq.jaiswal97@gmail.com> * docs: fix API key link and remove neural/keyword search type references Co-Authored-By: Tanishq Jaiswal <tanishq.jaiswal97@gmail.com> * docs: add instant, fast, auto, deep search types Co-Authored-By: Tanishq Jaiswal <tanishq.jaiswal97@gmail.com> --------- Co-authored-by: João Moura <joaomdmoura@gmail.com>	2026-03-17 12:27:41 -03:00
João Moura Claude Opus 4.5 alex-clawd	6235810844	fix: enhance LLM response handling and serialization (#4909 ) CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Mark stale issues and pull requests / stale (push) Has been cancelled Details * fix: enhance LLM response handling and serialization * Updated the Flow class to improve error handling when both structured and simple prompting fail, ensuring the first outcome is returned as a fallback. * Introduced a new function, _serialize_llm_for_context, to properly serialize LLM objects with provider prefixes for better context management. * Added tests to validate the new serialization logic and ensure correct behavior when LLM calls fail. This update enhances the robustness of LLM interactions and improves the overall flow of handling outcomes. * fix: patch VCR response handling to prevent httpx.ResponseNotRead errors (#4917) * fix: enhance LLM response handling and serialization * Updated the Flow class to improve error handling when both structured and simple prompting fail, ensuring the first outcome is returned as a fallback. * Introduced a new function, _serialize_llm_for_context, to properly serialize LLM objects with provider prefixes for better context management. * Added tests to validate the new serialization logic and ensure correct behavior when LLM calls fail. This update enhances the robustness of LLM interactions and improves the overall flow of handling outcomes. * fix: patch VCR response handling to prevent httpx.ResponseNotRead errors VCR's _from_serialized_response mocks httpx.Response.read(), which prevents the response's internal _content attribute from being properly initialized. When OpenAI's client (using with_raw_response) accesses response.content, httpx raises ResponseNotRead. This patch explicitly sets response._content after the response is created, ensuring that tests using VCR cassettes work correctly with the OpenAI client's raw response handling. Fixes tests: - test_hierarchical_crew_creation_tasks_with_sync_last - test_conditional_task_last_task_when_conditional_is_false - test_crew_log_file_output Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com> --------- Co-authored-by: Joao Moura <joaomdmoura@gmail.com> Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com> --------- Co-authored-by: alex-clawd <alex@crewai.com> Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>	2026-03-17 05:19:31 -03:00
Matt Aitchison	b95486c187	fix: upgrade vulnerable transitive dependencies (authlib, PyJWT, snowflake-connector-python) (#4913 ) CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details Build uv cache / build-cache (3.10) (push) Has been cancelled Details Build uv cache / build-cache (3.11) (push) Has been cancelled Details Build uv cache / build-cache (3.12) (push) Has been cancelled Details Build uv cache / build-cache (3.13) (push) Has been cancelled Details Nightly Canary Release / Check for new commits (push) Has been cancelled Details Nightly Canary Release / Build nightly packages (push) Has been cancelled Details Nightly Canary Release / Publish nightly to PyPI (push) Has been cancelled Details - authlib 1.6.7 → 1.6.9 (CVE-2026-27962 critical, CVE-2026-28498, CVE-2026-28490) - PyJWT 2.11.0 → 2.12.1 (CVE-2026-32597) - snowflake-connector-python 4.2.0 → 4.3.0	2026-03-16 19:02:39 -05:00
Lucas Gomide	ead8e8d6e6	docs: add Custom MCP Servers in How-To Guide (#4911 )	2026-03-16 17:01:41 -04:00
Vini Brasil	5bbf9c8e03	Update OTEL collectors documentation (#4908 ) CodeQL Advanced / Analyze (actions) (push) Has been cancelled Details CodeQL Advanced / Analyze (python) (push) Has been cancelled Details Check Documentation Broken Links / Check broken links (push) Has been cancelled Details * Update OTEL collectors documentation * Add translations	2026-03-16 13:27:57 -03:00