modelcontextprotocol / modelcontextprotocol/python-sdk
client's `read_stream_writer` open after SSE disconnection hanging `.receive()`
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Description
Initial Checks
- I confirm that I'm using the latest version of MCP Python SDK
- I confirm that I searched for my issue in https://github.com/modelcontextprotocol/python-sdk/issues before opening this issue
Description
This issue MAY be related to the following
- https://github.com/modelcontextprotocol/python-sdk/issues/1805
- https://github.com/modelcontextprotocol/python-sdk/issues/1764
- https://github.com/modelcontextprotocol/python-sdk/issues/262
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
httpxtimeout) - 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
BrokenResourceErrorbecause 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:
ssetimeout should always be greater or equal to the expected timeout of tool calls (now thatsse_read_timeoutis deprecated it'shttpx.Timeoutcounterpart 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.
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`
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Piste de recherche
Commencez dans src/mcp/client/streamable_http.py autour des lignes 433-435 et reproduisez l’appel qui se bloque avec l’exemple Python utilisant StreamableHttpTransport. Suivez la manière dont le délai d’attente de lecture SSE ferme la connexion et dont la session consomme les messages de read_stream_writer. C’est terminé lorsque l’appel client retourne ou lève une exception après l’expiration du délai, au lieu de rester bloqué indéfiniment.
Rédigé par le modèle d'indexation à partir du texte de l'issue.
Évaluation
- Stack technique
- python
- Domaine
- api, networking
- Type d'issue
- Bug
- Difficulté
- 3/5
- Temps estimé
- 1-2 jours
- Activité
- À l'abandon
- Clarté
- Plutôt claire
- Accessibilité débutants
- 42/100