LEADER: modelcontextprotocol/python-sdk
URL: https://github.com/modelcontextprotocol/python-sdk
License: MIT
License SHA (blob): 3d48435454b105021b4f777c11b6b07d8d2ffea3
HEAD commit (main): 161834d4aee2633c42d3976c8f8751b6c4d947d5
Commit date: 2026-05-08T16:42:44Z
Why chosen
| Criterion | python-sdk | gorilla |
|---|---|---|
| License | MIT ✓ | Apache-2.0 ✓ |
| Dispatch primitive | session.call_tool(name, args) — 1 RPC call |
OpenFunctions requires inference server |
| Kernel extractability | Pure Python, sync-wrappable | Coupled to model weights |
| Mockability | invoke callable injection trivial |
Requires HTTP stub |
| Dependency footprint | anyio + pydantic |
torch / vLLM |
Decision: python-sdk wins. Its ToolManager.call_tool(name, args, context) pattern reduces to a single dict lookup + async run — extractable to ≤10 sync lines with a mockable callable injected at the boundary. gorilla/OpenFunctions is powerful for LLM-driven selection but mandates a model server, violating the kernel-size constraint.
Dispatch anatomy (from source)
src/mcp/client/session.py → ClientSession.call_tool(name, args)
src/mcp/server/mcpserver/tools/tool_manager.py → ToolManager.call_tool(name, args, ctx)
src/mcp/server/mcpserver/tools/base.py → Tool.run(args, ctx)
Core pattern: tool = registry[name]; result = tool.fn(**args). Everything else is schema validation and async transport — stripped in the kernel.