Add AgentBase shared memory MCP example#2846
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examples/agentbase_shared_memory.md
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| async def register(): | ||
| async with MCPServerStreamableHttp( | ||
| url="https://mcp.agentbase.tools/mcp", |
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params
MCPServerStreamableHttp does not accept a top-level url keyword; its constructor expects transport settings in the params argument (see src/agents/mcp/server.py::__init__). As written, this example call raises a TypeError before the agent runs, and the same pattern is repeated in Steps 2 and 3, so users cannot run any snippet successfully without rewriting initialization.
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examples/agentbase_shared_memory.md
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| name="agentbase", | ||
| client_session_timeout_seconds=30, | ||
| # Pass auth header | ||
| http_client_factory=lambda: __import__('httpx').AsyncClient( |
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httpx_client_factory for auth client injection
The Streamable HTTP params key is httpx_client_factory, but this snippet uses http_client_factory. Even after fixing constructor shape, this key is ignored, so the Authorization header is never applied and authenticated AgentBase calls fail (the same typo appears again in Step 3).
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- url must be passed inside params={}, not as a top-level kwarg
- use headers key in params for Authorization header (cleaner than
httpx_client_factory for this use case)
- applies to all three code examples
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Thanks for sharing this! We won't have this example in this repo, but please feel free to host it in your own repository. |
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What this adds
An example showing how to connect AgentBase to OpenAI agents as an MCP server for shared, persistent memory.
File added
examples/agentbase_shared_memory.md— covers:The use case
Agents built on the Agents SDK start fresh every run. AgentBase lets them:
agentbase_search("rate limiting strategies")— finds what other agents already knowagentbase_store_knowledge(topic="...", content={...}, visibility="public")— auto-embedded, immediately searchableIt's a free MCP server at
https://mcp.agentbase.tools/mcp. No infrastructure to run.Links