modelcontextprotocol / modelcontextprotocol/python-sdk

client's `read_stream_writer` open after SSE disconnection hanging `.receive()`

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Descripción

Initial Checks
Description

This issue MAY be related to the following

Experiencing deadlocks on streamable_http transport. In order to reproduce the issue the following can be run.

import asyncio
import logging
import threading
import time

from fastmcp import Client, FastMCP
from fastmcp.client.transports import StreamableHttpTransport

logging.basicConfig(
    level=logging.DEBUG,
    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
    handlers=[logging.StreamHandler()],
)

logger = logging.getLogger(__name__)

HOST = "127.0.0.1"
PORT = 8765
SERVER_URL = f"http://{HOST}:{PORT}/mcp"

mcp = FastMCP(name="timeout issue")

SSE_TIMEOUT = 0.1
SLEEP = 60


@mcp.tool
def blocking_call() -> str:
    time.sleep(SLEEP)
    return "42"


def run_server():
    mcp.run(transport="streamable-http", host=HOST, port=PORT)


async def test_blocking_sse():
    transport = StreamableHttpTransport(SERVER_URL, sse_read_timeout=SSE_TIMEOUT)
    async with Client(transport) as client:
        tools = await client.list_tools()
        print(f"available tools: {[t.name for t in tools]}")
        result = await client.call_tool("blocking_call", {})
        print(f"blocking result: {result}")


if __name__ == "__main__":
    server_thread = threading.Thread(target=run_server, daemon=True)
    server_thread.start()

    time.sleep(2)

    try:
        asyncio.run(test_blocking_sse())
    finally:
        logger.info(f"{time.strftime('%Y-%m-%d %H:%M:%S')} [CLIENT] Shutting down...")

Execution context := locally built fastmcp at this commit 790ea92

Observed Behavior: the client hangs forever after the SSE read timeout fires, looking at the logs:

  • tool request is sent, server returns HTTP 200 with [Content-Type: text/event-stream]
  • server starts executing the tool (blocking time.sleep(60))
  • client's SSE read timeout fires (after ~5 seconds with default httpx timeout)
  • client closes the HTTP connection
  • client hangs indefinitely - call_tool() never returns
  • the tool eventually completes on the server side, but when the server tries to send the response back, it gets BrokenResourceError because the HTTP connection was already closed by the client.

I know noting about nothing, so I can imagine the above example is just an issue on my side, maybe:

  • sse timeout should always be greater or equal to the expected timeout of tool calls (now that sse_read_timeout is deprecated it's httpx.Timeout counterpart should be >= tool timeout)
  • long running tool calls MUST send progress updates

but one thing is for sure and that is, the above configuration hangs indefenitely because the session layer never gets to know that the transport layer is dead after the SSE stream is closed

Within my ignorance of many aspects of the implementation, the missing else branch seems to be the root cause.

https://github.com/modelcontextprotocol/python-sdk/blob/a9cc822a1051b1bd2b6b9b57e9e4136406983b61/src/mcp/client/streamable_http.py#L433-L435

and the fix looks something like

if last_event_id is not None:  # pragma: no branch 
    ...
else:
    error_response = JSONRPCError(...)
    await ctx.read_stream_writer.send(SessionMessage(JSONRPCMessage(root=error_response)))

consequently raising McpError

Example Code

Python & MCP Python SDK
Execution context for ease of implementation 
- `mcp==1.24.0`
- example codebase run against locally built `fastmcp` at [790ea92](https://github.com/jlowin/fastmcp/tree/790ea92eb59256da68c83097321ebde8f8819bcf) --> 1.24.0
- Python: `python-3.12.7-macos-aarch64-none/bin/python3.12`

Guía de contribución

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Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  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 src/mcp/client/streamable_http.py alrededor de las líneas 433-435 y reproduce la llamada que se queda bloqueada con el ejemplo de Python usando StreamableHttpTransport. Traza cómo el tiempo de espera de lectura de SSE cierra la conexión y cómo la sesión consume los mensajes de read_stream_writer. Se considera terminado cuando la llamada del cliente retorna o lanza una excepción después del tiempo de espera, en lugar de quedarse bloqueada indefinidamente.

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

Evaluación

Stack tecnológico
python
Área
api, networking
Tipo de issue
Error
Dificultad
3/5
Tiempo estimado
1-2 días
Estado de actividad
Estancado
Claridad
Bastante claro
Aptitud para principiantes
42/100

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