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Optimized Memory MCP Server V2

by AgentWong
base.py2.84 kB
import inspect from typing import TYPE_CHECKING, Any, Callable from pydantic import BaseModel, Field import mcp.server.fastmcp from mcp.server.fastmcp.exceptions import ToolError from mcp.server.fastmcp.utilities.func_metadata import FuncMetadata, func_metadata if TYPE_CHECKING: from mcp.server.fastmcp.server import Context class Tool(BaseModel): """Internal tool registration info.""" fn: Callable = Field(exclude=True) name: str = Field(description="Name of the tool") description: str = Field(description="Description of what the tool does") parameters: dict = Field(description="JSON schema for tool parameters") fn_metadata: FuncMetadata = Field( description="Metadata about the function including a pydantic model for tool" " arguments" ) is_async: bool = Field(description="Whether the tool is async") context_kwarg: str | None = Field( None, description="Name of the kwarg that should receive context" ) @classmethod def from_function( cls, fn: Callable, name: str | None = None, description: str | None = None, context_kwarg: str | None = None, ) -> "Tool": """Create a Tool from a function.""" func_name = name or fn.__name__ if func_name == "<lambda>": raise ValueError("You must provide a name for lambda functions") func_doc = description or fn.__doc__ or "" is_async = inspect.iscoroutinefunction(fn) # Find context parameter if it exists if context_kwarg is None: sig = inspect.signature(fn) for param_name, param in sig.parameters.items(): if param.annotation is mcp.server.fastmcp.Context: context_kwarg = param_name break func_arg_metadata = func_metadata( fn, skip_names=[context_kwarg] if context_kwarg is not None else [], ) parameters = func_arg_metadata.arg_model.model_json_schema() return cls( fn=fn, name=func_name, description=func_doc, parameters=parameters, fn_metadata=func_arg_metadata, is_async=is_async, context_kwarg=context_kwarg, ) async def run(self, arguments: dict, context: "Context | None" = None) -> Any: """Run the tool with arguments.""" try: return await self.fn_metadata.call_fn_with_arg_validation( self.fn, self.is_async, arguments, {self.context_kwarg: context} if self.context_kwarg is not None else None, ) except Exception as e: raise ToolError(f"Error executing tool {self.name}: {e}") from e

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