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Simple chatbot: consider removing cleanup lock from sequential lifecycle

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2/5
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1-3 小时
新手友好度
66/100
Issue 类型
重构
描述清晰度
基本清楚
活跃度
活跃
技术栈
python
领域
backend

调研方向

从 examples/clients/simple-chatbot/mcp_simple_chatbot/main.py 开始,沿着 issue 中描述的清理调用路径进行追踪。在移除锁之前,向维护者确认是否应支持演示流程之外的并发调用方。完成标准是:移除锁,同时保留现有的清理主体和错误处理;或者添加注释,说明预期的并发使用场景。

由索引模型根据 Issue 内容生成。

描述

enhancement

While studying the simple chatbot's context-management lifecycle, I found Server._cleanup_lock confusing because the example does not appear to invoke cleanup concurrently on the same Server.

Source: examples/clients/simple-chatbot/mcp_simple_chatbot/main.py.

The current call paths are sequential:

  • Server.initialize() awaits self.cleanup() on initialization failure before re-raising.
  • ChatSession.start() awaits cleanup_servers() in its initialization-error handler and again in its finally block.
  • cleanup_servers() awaits each server's cleanup in reverse server order.

Repeated cleanup calls therefore do not overlap in the demonstrated flow. A single AsyncExitStack.aclose() already awaits the registered exits sequentially in reverse order, so the lock is not needed to make session teardown precede transport teardown.

Suggested simplification: remove the _cleanup_lock initialization and the async with self._cleanup_lock: wrapper, retaining the existing cleanup body and error handling. Alternatively, a brief comment explaining an intended concurrent-caller use case would clarify why the lock is retained.

This is an example-code clarity/simplification request based on source inspection, not an observed runtime bug or a claim that locks are unnecessary for concurrent cleanup generally. Removing it would remove serialization for callers that use this class concurrently outside the demonstrated flow; that tradeoff needs maintainer judgment. No runtime tests were performed for this report.

Reporting first per the contribution guide. AI assistance: prepared with OpenAI Codex after discussing the example and inspecting its cleanup call paths.

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  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。

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