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