When using the MCP tool under langgraph_supervisor with LangGraph API Server, there are 1. Repeat loop bug; 2. Blocking in calling the tool

[zhenyu-24]

When I use MCP on a sub-agent under the supervisor multi-agent and test it with langgraph-cli, I find that 1. a repeated loop; 2. a blocking when calling a method. However, when running it locally, the results are returned normally, and when using the MCP tool on a single agent in langgraph-cli, the results also seem to be returned normally.


The test cases are：
1.List the files/folders under "/PATH"
2.SSH remote connection to the server and check the disk space

The code is as follows, some parameters need to be configured：

# graph.py
from contextlib import asynccontextmanager
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
from langgraph_supervisor import create_supervisor
from langchain.chat_models import init_chat_model

async def make_graph():
    MCP_DIR = r"xxxxxxxx"
    client = MultiServerMCPClient(
        {
            "desktop-commander": {
                "command": "npx",
                "args": [
                    "--no-install",
                    "--yes",
                    "@wonderwhy-er/desktop-commander",
                    "serve",
                    "--no-onboarding"
                ],
                "transport": "stdio",
                "cwd": MCP_DIR
            },
            "ssh-mcp-server": {
                "command": "npx",
                "args": [
                    "--no-install",
                    "-y",
                    "@fangjunjie/ssh-mcp-server",
                    "--host", "xxxxxx",
                    "--port", "22",
                    "--username", "xxxxx",
                    "--password", "xxxxx",
                ],
                "transport": "stdio",
                "cwd": MCP_DIR
            }
        }
    )
    tools = await client.get_tools()
    Filesystem_tools = [t for t in tools if t.name in {
        'read_file', 'read_multiple_files', 'write_file', 'create_directory',
        'list_directory', 'move_file', 'get_file_info', 'edit_block',
        'start_search', 'stop_search', 'list_searches', 'get_more_search_results'
    }]
    Terminal_tools = [t for t in tools if t.name in {
        'start_process', 'read_process_output', 'interact_with_process',
        'force_terminate', 'list_sessions', 'list_processes', 'kill_process'
    }]
    SSH_tools = [t for t in tools if t.name in {
        'execute-command', 'upload', 'download', 'list-servers'
    }]
    llm = init_chat_model(
        model="qwen3:14b",
        model_provider="ollama",
        base_url="http://localhost:11434",
    )
    filesystem_agent = create_react_agent(
        llm,
        tools=Filesystem_tools,
        prompt="""xxxxxx""",
        name="filesystem_agent",
    )
    terminal_agent = create_react_agent(
        llm,
        tools=Terminal_tools,
        prompt="""xxxxxx""",
        name="terminal_agent",
    )
    ssh_agent = create_react_agent(
        llm,
        tools=SSH_tools,
        prompt="""xxxxxx""",
        name="ssh_agent",
    )
    agent = create_supervisor(
        model=llm,
        agents=[filesystem_agent, terminal_agent, ssh_agent],
        prompt='xxxxxx',
        add_handoff_back_messages=True,
        output_mode="full_history",
    ).compile()
    return agent

if __name__ == '__main__':
    # 'langgraph dev --allow-blocking'
    import asyncio
    async def main():
        graph = await make_graph()
        result = await graph.ainvoke(
            input={"messages": [{"role": "user", "content": r"SSH remote connection to the server and check the disk space"}]}
        )
        print("Agent Invocation Result:")
        print(result)
    asyncio.run(main())