Files
crewAI/docs/edge/ar/mcp/streamable-http.mdx
Lucas Gomide 93dafe2637 feat: adopt directory-based docs versioning with Edge channel
Switch docs.crewai.com from navigation-only versioning (every version
selector entry rendered the same docs/<lang>/* source files) to
Mintlify's directory-based versioning so each version selector entry
renders its own snapshot. Add an "Edge" channel under docs/edge/<lang>/*
that always reflects main HEAD for unreleased work, eliminating
pre-release leakage onto frozen release labels. External links to
canonical /<lang>/* URLs are preserved via wildcard redirects that
always land on the current default version.

Layout:
- docs/edge/<lang>/*         rolling source (you edit here)
- docs/edge/enterprise-api.*.yaml
- docs/v<X.Y.Z>/<lang>/*     frozen, immutable snapshots
- docs/v<X.Y.Z>/enterprise-api.*.yaml
- docs/images/               shared, append-only
- docs/docs.json             nav + redirects

URLs follow the Mintlify-idiomatic shape: /edge/<lang>/<page> for
Edge, /v<X.Y.Z>/<lang>/<page> for every frozen snapshot. The wildcard
redirects /<lang>/:slug* -> /<default>/<lang>/:slug* keep stale links
working, and every freeze rewrites them (plus all per-section/per-page
redirects) so destinations always resolve to the current default
without depending on a second redirect hop.

Release flow integration (devtools release):
- New module crewai_devtools.docs_versioning.freeze() materialises
  docs/v<X.Y.Z>/ from docs/edge/, rewrites openapi: refs inside the
  snapshot, inserts the version into every language block in
  docs.json, and refreshes all redirect destinations.
- _update_docs_and_create_pr() in cli.py now calls that freeze during
  Phase 2 of devtools release. Edge changelogs are updated first (so
  the snapshot freeze picks them up), then the snapshot is staged
  alongside docs.json, branched as docs/freeze-v<X.Y.Z>, and the PR
  is titled [docs-freeze] docs: snapshot and changelog for v<X.Y.Z>
  — the title prefix the new CI guard reads.
- The PR still gates tag, GitHub release, PyPI publish, and the
  enterprise release as before; no new PRs are added.
- Pre-releases (1.X.YaN, 1.X.YbN, ...) skip the snapshot — they ride
  Edge — and the docs PR title omits the [docs-freeze] prefix.
- docs_check (AI-generated docs scaffolding) writes to
  docs/edge/<lang>/* so newly-generated unreleased docs land in Edge
  and never accidentally touch a frozen snapshot.

Migration scripts (one-shot):
- scripts/docs/freeze_historical_versions.py reconstructs all 16
  historical snapshots (v1.10.0 .. v1.14.7) from git tags via
  git archive | tar, rewriting openapi: MDX refs so each snapshot
  reads its own enterprise-api YAML rather than the live one.
- scripts/docs/prefix_version_paths.py one-shot-migrates docs.json:
  rewrites every page path in 16 versioned blocks to point under
  docs/v<X.Y.Z>/, inserts a new Edge entry per language, tags
  v1.14.7 as Latest (default), prunes pages whose target file
  doesn't exist in the snapshot (e.g. docs/ar/ didn't exist before
  v1.12.0), and writes the wildcard + per-section redirects.
- scripts/docs/freeze_current_edge.py is now a thin CLI wrapper
  around docs_versioning.freeze for manual one-off freezes (e.g.
  retroactively snapshotting a forgotten release).

CI guards (.github/workflows/docs-snapshots.yml):
- Frozen snapshots under docs/v[0-9]*/ are immutable; only PRs whose
  title contains [docs-freeze] (i.e. release-cut PRs generated by
  devtools release or the manual wrapper) may modify them.
- Images under docs/images/ are append-only since snapshots share a
  single image directory. Deleting or renaming an image breaks every
  historical snapshot that still references it.

Restored docs/images/crewai-otel-export.png from PR #3673; it was
deleted in PR #4908 but v1.10.0 / v1.10.1 snapshots still reference
it. Restoring instead of editing the snapshots preserves historical
rendering fidelity and validates the new append-only rule
retroactively.

Tests:
- lib/devtools/tests/test_docs_versioning.py covers the freeze: file
  copy, openapi rewrite, version insertion, default demotion, redirect
  upserts, per-section redirect rewriting, idempotency, and invalid
  inputs.

Verified locally with mintlify broken-links: 0 broken links across
the full site (Edge + 16 frozen versions, 4 locales).

AGENTS.md (repo root) is the contributor guide for the new model;
RELEASING.md is the release-cut runbook; README's Contribution
section links to both.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-17 11:08:45 -03:00

137 lines
6.1 KiB
Plaintext

---
title: نقل Streamable HTTP
description: تعلم كيفية ربط CrewAI بخوادم MCP البعيدة باستخدام نقل Streamable HTTP المرن.
icon: globe
mode: "wide"
---
## نظرة عامة
يوفر نقل Streamable HTTP طريقة مرنة للاتصال بخوادم MCP البعيدة. يُبنى عادةً على HTTP ويمكنه دعم أنماط اتصال متنوعة، بما في ذلك الطلب والاستجابة والبث، وأحياناً يستخدم Server-Sent Events (SSE) لتدفقات من الخادم إلى العميل ضمن تفاعل HTTP أوسع.
## المفاهيم الرئيسية
- **خوادم بعيدة**: مصمم لخوادم MCP المستضافة عن بُعد.
- **المرونة**: يمكنه دعم أنماط تفاعل أكثر تعقيداً من SSE العادي، بما في ذلك الاتصال ثنائي الاتجاه المحتمل إذا نفذه الخادم.
- **إعداد `MCPServerAdapter`**: ستحتاج إلى توفير عنوان URL الأساسي للخادم للاتصال MCP وتحديد `"streamable-http"` كنوع النقل.
## الاتصال عبر Streamable HTTP
لديك طريقتان رئيسيتان لإدارة دورة حياة الاتصال مع خادم MCP Streamable HTTP:
### 1. اتصال مُدار بالكامل (الموصى به)
النهج الموصى به هو استخدام مدير سياق Python (تعليمة `with`)، الذي يتعامل مع إعداد الاتصال وإنهائه تلقائياً.
```python
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
server_params = {
"url": "http://localhost:8001/mcp", # Replace with your actual Streamable HTTP server URL
"transport": "streamable-http"
}
try:
with MCPServerAdapter(server_params) as tools:
print(f"Available tools from Streamable HTTP MCP server: {[tool.name for tool in tools]}")
http_agent = Agent(
role="HTTP Service Integrator",
goal="Utilize tools from a remote MCP server via Streamable HTTP.",
backstory="An AI agent adept at interacting with complex web services.",
tools=tools,
verbose=True,
)
http_task = Task(
description="Perform a complex data query using a tool from the Streamable HTTP server.",
expected_output="The result of the complex data query.",
agent=http_agent,
)
http_crew = Crew(
agents=[http_agent],
tasks=[http_task],
verbose=True,
process=Process.sequential
)
result = http_crew.kickoff()
print("\nCrew Task Result (Streamable HTTP - Managed):\n", result)
except Exception as e:
print(f"Error connecting to or using Streamable HTTP MCP server (Managed): {e}")
print("Ensure the Streamable HTTP MCP server is running and accessible at the specified URL.")
```
**ملاحظة:** استبدل `"http://localhost:8001/mcp"` بعنوان URL الفعلي لخادم MCP Streamable HTTP الخاص بك.
### 2. دورة حياة اتصال يدوية
للسيناريوهات التي تتطلب تحكماً أكثر صراحة، يمكنك إدارة اتصال `MCPServerAdapter` يدوياً.
<Info>
من **الضروري** استدعاء `mcp_server_adapter.stop()` عند الانتهاء لإغلاق الاتصال وتحرير الموارد. كتلة `try...finally` هي الطريقة الأكثر أماناً لضمان ذلك.
</Info>
```python
from crewai import Agent, Task, Crew, Process
from crewai_tools import MCPServerAdapter
server_params = {
"url": "http://localhost:8001/mcp", # Replace with your actual Streamable HTTP server URL
"transport": "streamable-http"
}
mcp_server_adapter = None
try:
mcp_server_adapter = MCPServerAdapter(server_params)
mcp_server_adapter.start()
tools = mcp_server_adapter.tools
print(f"Available tools (manual Streamable HTTP): {[tool.name for tool in tools]}")
manual_http_agent = Agent(
role="Advanced Web Service User",
goal="Interact with an MCP server using manually managed Streamable HTTP connections.",
backstory="An AI specialist in fine-tuning HTTP-based service integrations.",
tools=tools,
verbose=True
)
data_processing_task = Task(
description="Submit data for processing and retrieve results via Streamable HTTP.",
expected_output="Processed data or confirmation.",
agent=manual_http_agent
)
data_crew = Crew(
agents=[manual_http_agent],
tasks=[data_processing_task],
verbose=True,
process=Process.sequential
)
result = data_crew.kickoff()
print("\nCrew Task Result (Streamable HTTP - Manual):\n", result)
except Exception as e:
print(f"An error occurred during manual Streamable HTTP MCP integration: {e}")
print("Ensure the Streamable HTTP MCP server is running and accessible.")
finally:
if mcp_server_adapter and mcp_server_adapter.is_connected:
print("Stopping Streamable HTTP MCP server connection (manual)...")
mcp_server_adapter.stop() # **Crucial: Ensure stop is called**
elif mcp_server_adapter:
print("Streamable HTTP MCP server adapter was not connected. No stop needed or start failed.")
```
## اعتبارات الأمان
عند استخدام نقل Streamable HTTP، فإن أفضل ممارسات أمان الويب العامة ضرورية:
- **استخدم HTTPS**: فضّل دائماً HTTPS لعناوين URL خوادم MCP لتشفير البيانات أثناء النقل.
- **المصادقة**: نفّذ آليات مصادقة قوية إذا كان خادم MCP يكشف أدوات أو بيانات حساسة.
- **التحقق من المدخلات**: تأكد من أن خادم MCP يتحقق من جميع الطلبات والمعاملات الواردة.
للحصول على دليل شامل حول تأمين تكاملات MCP، يرجى الرجوع إلى صفحة [اعتبارات الأمان](./security.mdx) ووثائق [أمان نقل MCP](https://modelcontextprotocol.io/docs/concepts/transports#security-considerations) الرسمية.