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Optimized Memory MCP Server V2

by AgentWong
websocket.py2.23 kB
import logging from contextlib import asynccontextmanager import anyio from anyio.streams.memory import MemoryObjectReceiveStream, MemoryObjectSendStream from starlette.types import Receive, Scope, Send from starlette.websockets import WebSocket import mcp.types as types logger = logging.getLogger(__name__) @asynccontextmanager async def websocket_server(scope: Scope, receive: Receive, send: Send): """ WebSocket server transport for MCP. This is an ASGI application, suitable to be used with a framework like Starlette and a server like Hypercorn. """ websocket = WebSocket(scope, receive, send) await websocket.accept(subprotocol="mcp") read_stream: MemoryObjectReceiveStream[types.JSONRPCMessage | Exception] read_stream_writer: MemoryObjectSendStream[types.JSONRPCMessage | Exception] write_stream: MemoryObjectSendStream[types.JSONRPCMessage] write_stream_reader: MemoryObjectReceiveStream[types.JSONRPCMessage] read_stream_writer, read_stream = anyio.create_memory_object_stream(0) write_stream, write_stream_reader = anyio.create_memory_object_stream(0) async def ws_reader(): try: async with read_stream_writer: async for message in websocket.iter_json(): try: client_message = types.JSONRPCMessage.model_validate(message) except Exception as exc: await read_stream_writer.send(exc) continue await read_stream_writer.send(client_message) except anyio.ClosedResourceError: await websocket.close() async def ws_writer(): try: async with write_stream_reader: async for message in write_stream_reader: obj = message.model_dump( by_alias=True, mode="json", exclude_none=True ) await websocket.send_json(obj) except anyio.ClosedResourceError: await websocket.close() async with anyio.create_task_group() as tg: tg.start_soon(ws_reader) tg.start_soon(ws_writer) yield (read_stream, write_stream)

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