MCP

MCP is a provider-adaptive capability and the primary entry point for MCP in Pydantic AI. It runs the MCP server locally by default — keeping credentials, hooks, and tracing under your control — and supports both URL-based servers and direct client / toolset / transport inputs.

Backed by MCPServerTool on the native side (see MCP Server Tool for provider support and configuration) — pass native=MCPServerTool(...) directly when you need full control (e.g. a different id, authorization_token, or description than the capability would derive). On the local side, local= accepts any MCPToolset input (URL, fastmcp.Client, transport, in-process FastMCP server, script path, …) — non-toolset inputs are wrapped in MCPToolset automatically.

mcp.py

from pydantic_ai.capabilities import MCP
from pydantic_ai.native_tools import MCPServerTool

# URL-based MCP server, running locally (requires `pydantic-ai-slim[mcp]`)
MCP('https://mcp.example.com/api')

# Local client without a URL — pass any `MCPToolset` input
# (URL, `fastmcp.Client`, transport, in-process `FastMCP` server, script path, etc.)
MCP(local=my_fastmcp_client)

# Native preferred; URL-based local fallback
MCP('https://mcp.example.com/api', native=True)

# Strict native-only (no local — does not require the `mcp` extra)
MCP('https://mcp.example.com/api', native=True, local=False)

# Explicit native + explicit local — independent configuration on each side
# (e.g. provider-relay URL for native, direct connection for local)
MCP(
    native=MCPServerTool(
        id='public-mcp',
        url='https://relay.example.com/mcp',
        authorization_token='relay-token',
    ),
    local=my_fastmcp_client,
)

For lower-level access — managing the MCPToolset lifecycle directly, advanced transport / client configuration, or using MCP servers without going through a capability — see the MCP documentation.