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* 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> * style: resolve linter issues --------- Co-authored-by: Cursor <cursoragent@cursor.com>
152 lines
5.7 KiB
Plaintext
152 lines
5.7 KiB
Plaintext
---
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title: SSE Transport
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description: Learn how to connect CrewAI to remote MCP servers using Server-Sent Events (SSE) for real-time communication.
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icon: wifi
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mode: "wide"
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---
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## Overview
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Server-Sent Events (SSE) provide a standard way for a web server to send updates to a client over a single, long-lived HTTP connection. In the context of MCP, SSE is used for remote servers to stream data (like tool responses) to your CrewAI application in real-time.
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## Key Concepts
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- **Remote Servers**: SSE is suitable for MCP servers hosted remotely.
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- **Unidirectional Stream**: Typically, SSE is a one-way communication channel from server to client.
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- **`MCPServerAdapter` Configuration**: For SSE, you'll provide the server's URL and specify the transport type.
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## Connecting via SSE
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You can connect to an SSE-based MCP server using two main approaches for managing the connection lifecycle:
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### 1. Fully Managed Connection (Recommended)
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Using a Python context manager (`with` statement) is the recommended approach. It automatically handles establishing and closing the connection to the SSE MCP server.
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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:8000/sse", # Replace with your actual SSE server URL
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"transport": "sse"
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}
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# Using MCPServerAdapter with a context manager
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try:
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with MCPServerAdapter(server_params) as tools:
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print(f"Available tools from SSE MCP server: {[tool.name for tool in tools]}")
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# Example: Using a tool from the SSE MCP server
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sse_agent = Agent(
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role="Remote Service User",
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goal="Utilize a tool provided by a remote SSE MCP server.",
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backstory="An AI agent that connects to external services via SSE.",
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tools=tools,
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reasoning=True,
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verbose=True,
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)
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sse_task = Task(
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description="Fetch real-time stock updates for 'AAPL' using an SSE tool.",
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expected_output="The latest stock price for AAPL.",
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agent=sse_agent,
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markdown=True
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)
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sse_crew = Crew(
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agents=[sse_agent],
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tasks=[sse_task],
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verbose=True,
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process=Process.sequential
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)
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if tools: # Only kickoff if tools were loaded
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result = sse_crew.kickoff() # Add inputs={'stock_symbol': 'AAPL'} if tool requires it
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print("\nCrew Task Result (SSE - Managed):\n", result)
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else:
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print("Skipping crew kickoff as tools were not loaded (check server connection).")
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except Exception as e:
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print(f"Error connecting to or using SSE MCP server (Managed): {e}")
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print("Ensure the SSE MCP server is running and accessible at the specified URL.")
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```
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<Note>
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Replace `"http://localhost:8000/sse"` with the actual URL of your SSE MCP server.
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</Note>
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### 2. Manual Connection Lifecycle
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If you need finer-grained control, you can manage the `MCPServerAdapter` connection lifecycle manually.
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<Info>
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You **MUST** call `mcp_server_adapter.stop()` to ensure the connection is closed and resources are released. Using a `try...finally` block is highly recommended.
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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:8000/sse", # Replace with your actual SSE server URL
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"transport": "sse"
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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 SSE): {[tool.name for tool in tools]}")
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manual_sse_agent = Agent(
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role="Remote Data Analyst",
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goal="Analyze data fetched from a remote SSE MCP server using manual connection management.",
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backstory="An AI skilled in handling SSE connections explicitly.",
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tools=tools,
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verbose=True
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)
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analysis_task = Task(
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description="Fetch and analyze the latest user activity trends from the SSE server.",
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expected_output="A summary report of user activity trends.",
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agent=manual_sse_agent
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)
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analysis_crew = Crew(
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agents=[manual_sse_agent],
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tasks=[analysis_task],
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verbose=True,
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process=Process.sequential
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)
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result = analysis_crew.kickoff()
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print("\nCrew Task Result (SSE - Manual):\n", result)
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except Exception as e:
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print(f"An error occurred during manual SSE MCP integration: {e}")
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print("Ensure the SSE 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 SSE 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("SSE MCP server adapter was not connected. No stop needed or start failed.")
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```
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## Security Considerations for SSE
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<Warning>
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**DNS Rebinding Attacks**: SSE transports can be vulnerable to DNS rebinding attacks if the MCP server is not properly secured. This could allow malicious websites to interact with local or intranet-based MCP servers.
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</Warning>
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To mitigate this risk:
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- MCP server implementations should **validate `Origin` headers** on incoming SSE connections.
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- When running local SSE MCP servers for development, **bind only to `localhost` (`127.0.0.1`)** rather than all network interfaces (`0.0.0.0`).
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- Implement **proper authentication** for all SSE connections if they expose sensitive tools or data.
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For a comprehensive overview of security best practices, please refer to our [Security Considerations](./security.mdx) page and the official [MCP Transport Security documentation](https://modelcontextprotocol.io/docs/concepts/transports#security-considerations).
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