modelcontextprotocol / modelcontextprotocol/python-sdk

`stdio_server` uses unbuffered memory streams which can cause server to block and become unresponsive

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bug P2 ready for work
Lenguaje dominante
Python
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Descripción

Initial Checks
Description

The MCP Python SDK's stdio_server becomes unresponsive during slow message processing operations, causing ping and/or new requests to timeout.

Observed Behaviour
  • Server appears to 'freeze' and becomes unresponsive after running for extended periods
  • Ping requests timeout during slow operations
  • New requests cannot be processed while the server is handling long-running operations
  • After 67 minutes of operation with requests every 10 seconds, the server became completely unresponsive
Expected Behaviour
  • Server should remain responsive to new requests (like pings) even while processing slow operations
  • Ping requests should not timeout due to message processing delays
  • The server should handle concurrent requests without blocking
Suspected Root Cause

The stdio_server uses max_buffer_size=0 (supplied to anyio.create_memory_object_stream) by default, which creates synchronous handoff between the stdin reader and message processor.

See: https://github.com/modelcontextprotocol/python-sdk/blob/543961968c0634e93d919d509cce23a1d6a56c21/src/mcp/server/stdio.py#L57-L58

When the message processor is slow or blocked, the stdin reader cannot read new messages from stdin, making the server appear unresponsive.

Example Code
  import anyio
  import pytest


  @pytest.mark.anyio
  async def test_server_becomes_unresponsive_with_slow_processor():
      """Demonstrates how server becomes unresponsive during slow processing."""

      # Simulates stdio_server with default max_buffer_size=0 (synchronous handoff)
      send_stream, receive_stream = anyio.create_memory_object_stream(0)

      async def stdin_reader():
          # First message gets through
          await send_stream.send("request_1")

          # Second message (like a ping) blocks until first is fully processed
          await send_stream.send("ping")  # This will block for entire processing time!

      async def message_processor():
          # Process first message
          msg = await receive_stream.receive()

          # Simulate slow processing (database query, API call, etc.)
          await anyio.sleep(0.1)  # 100ms processing time

          # During this time, stdin_reader is completely blocked
          # No new messages (including pings) can be read!

          ping = await receive_stream.receive()  # Finally unblocks stdin_reader

      async with anyio.create_task_group() as tg:
          tg.start_soon(message_processor)
          await anyio.sleep(0.01)  # Let processor start waiting
          tg.start_soon(stdin_reader)

      send_stream.close()
      receive_stream.close()
Proposed Solution

Allow users to configure max_buffer_size > 0 to enable buffering, with a default value (0) that preserves the current behaviour.

async def stdio_server(
    stdin: anyio.AsyncFile[str] | None = None,
    stdout: anyio.AsyncFile[str] | None = None,
    max_buffer_size: int = 0, 
):
    # ...
    read_stream_writer, read_stream = anyio.create_memory_object_stream(max_buffer_size)
    write_stream, write_stream_reader = anyio.create_memory_object_stream(max_buffer_size)
Python & MCP Python SDK
  • Python: 3.12
  • MCP Python SDK: 1.12.4
  • OS: macOS
Additional Context

The issue manifests in long-running servers where message processing can occasionally be slow (database queries, file operations, API calls).

The fix should make max_buffer_size configurable so users can add buffering to prevent the stdin reader from blocking during slow operations.

Guía de contribución

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Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
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  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

Línea de trabajo

Comienza en la configuración referenciada de memory-stream en src/mcp/server/stdio.py e inspecciona cómo se pasa max_buffer_size a ambos streams. Haz que el tamaño del búfer sea configurable como se describe, conserva el valor predeterminado actual y verifica, usando el ejemplo asíncrono proporcionado, que un valor positivo permite almacenar en búfer la entrada durante un procesamiento lento.

Escrito por el modelo de indexación a partir del texto del issue.

Evaluación

Stack tecnológico
python
Área
backend
Tipo de issue
Error
Dificultad
2/5
Tiempo estimado
1-3 horas
Estado de actividad
Estancado
Claridad
Bien especificado
Aptitud para principiantes
52/100

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