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name: mcp description: "Expose LitServe LitAPI endpoints as Model Context Protocol tools with schema extraction, streamable HTTP mounting, and connection troubleshooting." metadata: disco-role: operating disable-model-invocation: true license: Apache 2.0

LitServe MCP sub-skill

Use this sub-skill when a user wants to expose a LitAPI as a Model Context Protocol (MCP) tool, build or debug the tool schema, mount the streamable HTTP MCP route, or connect an MCP client such as Claude Desktop to a LitServe app.

Routing

• Start here for requests like “add MCP to my LitServe app”, “make a tool from decode_request”, “why does MCP say it is not connected”, “mount the streamable HTTP MCP route”, or “build the MCP schema from Pydantic/type hints”.
• Use the root LitServe router at ../../SKILL.md when the request is broader than MCP.
• Use ../server-basics/SKILL.md when the user needs the underlying LitAPI, LitServer, request/response, batching, streaming, auth, middleware, or deployment model first.
• Route OpenAI-compatible chat and embedding endpoint work to ../openai-specs/SKILL.md.
• Do not cover benchmark-only, torch-heavy, parity-throughput, or accelerator-specific workflows here.

Operating checklist

1. Confirm the runtime has fastmcp installed. LitServe MCP construction raises a runtime error when MCP support packages are unavailable.
2. Create an MCP object with at least a useful description; optionally set a unique name and a manual input_schema.
3. Pass the MCP object into the LitAPI constructor (super().__init__(mcp=...) or a base class that accepts mcp). This connects the MCP object to the LitAPI; do not call private connection methods in user code.
4. Prefer automatic schema extraction from decode_request when the endpoint accepts a Pydantic request model or well-annotated parameters. Use a manual input_schema only when it matches the actual LitServe endpoint handler arguments.
5. Build the server with ls.LitServer(api) and run it normally. LitServe registers the tool and mounts the streamable HTTP MCP app automatically when MCP support is available.
6. Tell MCP clients to connect to the same host and port with the /mcp/ suffix, for example http://localhost:8000/mcp/.
7. If the client lists the tool but tool calls fail, debug the schema shape, tool name uniqueness, and endpoint path mapping before changing core server code.

Reference map

• references/api-reference.md — exact MCP constructor behavior, schema helper behavior, connector internals, and streamable HTTP route details.
• references/workflows.md — copyable patterns for adding MCP to a LitAPI, using Pydantic/type-hint schemas, checking the tool object, connecting clients, and Claude Desktop setup.
• references/troubleshooting.md — common failures: missing fastmcp, disconnected MCP, missing name/description, malformed schema, endpoint collisions, missing mounted route, beta warning, and Claude Desktop confusion.
• scripts/mcp_server.py — safe bundled example adapted from LitServe MCP behavior; it can print the generated tool metadata or run a local MCP-enabled LitServe server.

Facts to preserve

• MCP(description=None, input_schema=None, name=None) accepts description, input_schema, and name.
• extract_input_schema(func) -> dict[str, Any] is available from litserve.mcp.
• _python_type_to_json_schema and _param_name_to_title are available helper functions.
• MCP.as_tool() requires a connected LitAPI and returns a ToolEndpointType with name, description, inputSchema, and endpoint.
• The tool name is sanitized by removing a leading slash and replacing remaining slashes with underscores.
• The MCP streamable HTTP endpoint is /mcp/ on the LitServe server.
• MCP support is beta and its APIs may change.