Source code for airflow.providers.common.ai.toolsets.mcp

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"""MCP server toolset that resolves configuration from an Airflow connection."""

from __future__ import annotations

from typing import TYPE_CHECKING, Any

from pydantic_ai.toolsets.abstract import AbstractToolset, ToolsetTool
from typing_extensions import Self

if TYPE_CHECKING:
    from pydantic_ai._run_context import RunContext


[docs] class MCPToolset(AbstractToolset[Any]): """ Toolset that connects to an MCP server configured via an Airflow connection. Reads MCP server transport type, URL, command, and credentials from the connection via :class:`~airflow.providers.common.ai.hooks.mcp.MCPHook` and creates the appropriate PydanticAI MCP server instance. All ``AbstractToolset`` methods delegate to the underlying MCP server. This is the recommended way to use MCP servers in Airflow — it stores server configuration in Airflow connections (and secret backends) rather than hard-coding URLs and credentials in DAG code. If you prefer full PydanticAI control, you can pass MCP server instances directly to ``AgentOperator(toolsets=[...])``, since :class:`~pydantic_ai.mcp.MCPServerStreamableHTTP`, :class:`~pydantic_ai.mcp.MCPServerSSE`, and :class:`~pydantic_ai.mcp.MCPServerStdio` all implement ``AbstractToolset``. :param mcp_conn_id: Airflow connection ID for the MCP server. :param tool_prefix: Optional prefix prepended to tool names (e.g. ``"weather"`` → ``"weather_get_forecast"``). """ def __init__( self, mcp_conn_id: str, *, tool_prefix: str | None = None, ) -> None: self._mcp_conn_id = mcp_conn_id self._tool_prefix = tool_prefix self._server: Any = None @property
[docs] def id(self) -> str: return f"mcp-{self._mcp_conn_id}"
def _get_server(self) -> Any: if self._server is None: from airflow.providers.common.ai.hooks.mcp import MCPHook hook = MCPHook(mcp_conn_id=self._mcp_conn_id, tool_prefix=self._tool_prefix) self._server = hook.get_conn() return self._server
[docs] async def __aenter__(self) -> Self: await self._get_server().__aenter__() return self
[docs] async def __aexit__(self, *args: Any) -> bool | None: if self._server is not None: return await self._server.__aexit__(*args) return None
[docs] async def get_tools(self, ctx: RunContext[Any]) -> dict[str, ToolsetTool[Any]]: return await self._get_server().get_tools(ctx)
[docs] async def call_tool( self, name: str, tool_args: dict[str, Any], ctx: RunContext[Any], tool: ToolsetTool[Any], ) -> Any: return await self._get_server().call_tool(name, tool_args, ctx, tool)

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