modelcontextprotocol / modelcontextprotocol/python-sdk

RequestResponder.__exit__ leaks CancelledError on cancelled request, killing the stdio receive loop

未关闭
#2,610 3 条评论 0 个 reaction 已指派 0 人 在 GitHub 查看

还没有人认领这个 Issue。

bug needs confirmation P2 potentially close
主要语言
Python
星标
24.3k
派生
4k
平均合并
1 天 1 小时
30 天内合并 PR
31

描述

Summary

When a client sends notifications/cancelled for an in-flight request handled over stdio, the server's receive loop task group dies. The process stays alive but stops reading stdin, so every subsequent request hangs and the client eventually reports MCP error -32000: Connection closed. The bug is racy — it reproduces in roughly 40–80% of attempts depending on platform timing.

Affects: mcp 1.26.0 and 1.27.1 (latest at time of writing). Confirmed with FastMCP 3.1.x and the in-tree stdio server.

Reproduction

A standalone subprocess test is in mlorentedev/hive tests/test_transport_recovery.py. The relevant flow:

  1. initialize → ack
  2. notifications/initialized
  3. tools/call id=2
  4. notifications/cancelled for requestId=2 (within a few ms of step 3)
  5. Receive: {"id": 2, "error": {"code": 0, "message": "Request cancelled"}} ← OK
  6. tools/call id=3
  7. No response. Server is alive but proc.stdout.readline() hangs.

Root cause

mcp.shared.session.RequestResponder.__exit__:

def __exit__(self, exc_type, exc_val, exc_tb):
    try:
        if self._completed:
            self._on_complete(self)
    finally:
        self._entered = False
        ...
        self._cancel_scope.__exit__(exc_type, exc_val, exc_tb)  # ← (A)

When notifications/cancelled arrives, RequestResponder.cancel() calls self._cancel_scope.cancel() and sends the error response. The handler task catches the CancelledError in mcp/server/lowlevel/server.py (around line 766) and returns. The with responder: block then exits with exc_type=None while the cancel scope is still in cancelled state — at line (A), anyio's CancelScope.__exit__ re-raises CancelledError.

That exception bubbles up to:

async with anyio.create_task_group() as tg:
    async for message in session.incoming_messages:
        tg.start_soon(self._handle_message, ...)

…in Server._run. anyio task groups cancel all sibling tasks and propagate the cancellation. The receive loop is one of those sibling tasks, so it dies.

Suggested fix

Swallow the spurious cancellation when the responder has already sent its response:

def __exit__(self, exc_type, exc_val, exc_tb):
    try:
        if self._completed:
            self._on_complete(self)
    finally:
        self._entered = False
        if not self._cancel_scope:
            raise RuntimeError("No active cancel scope")
        try:
            self._cancel_scope.__exit__(exc_type, exc_val, exc_tb)
        except BaseException as exc:
            if self._completed and isinstance(exc, anyio.get_cancelled_exc_class()):
                # cancel() already sent the error response — the scope's
                # re-raised cancellation is spurious.
                return
            raise

Mirrors what we ship in hive src/hive/_compat.py.

Workaround used downstream

We monkey-patch RequestResponder.__exit__ at import time. The patch is self-gated (only fires when _completed=True AND the leaking exception is anyio.get_cancelled_exc_class()), so it stays inert once a fix lands upstream.

Environment

  • Reproduced on Windows 11 (mcp 1.26.0, 1.27.1) and via Claude Code as the host.
  • Tracked downstream in mlorentedev/hive#75.
  • Regression test passes 5/5 with the patch applied on Python 3.12; fails 2/5 — 4/5 without it.
  • Python 3.13 appears to have additional uncancel semantics that the patch does not yet fully cover — verification in progress.

贡献指南

打开贡献指南

从这里开始

  1. 先读完整个 Issue,再读项目的贡献指南。
  2. 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
  3. Fork 仓库,在一个分支上完成修改。
  4. 提交 Pull Request,并在描述里引用这个 Issue 编号。

调研方向

从 mcp.shared.session.RequestResponder.exit 开始,检查 mcp/server/lowlevel/server.py 第 766 行附近的取消处理。使用 tests/test_transport_recovery.py 重现,然后验证取消一个 stdio 请求仍会生成其错误响应,并且后续请求能够收到响应,而不会导致接收循环停止。

由索引模型根据 Issue 内容生成。

评估

技术栈
python
领域
api, backend
Issue 类型
缺陷
难度
3/5
预计耗时
1-2 天
活跃度
冷清
描述清晰度
描述清楚
新手友好度
68/100

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。