simple-testing-mcp

Minimal FastMCP server managed with uv.

Requirements

• Python 3.12+

• uv

• Docker (optional)

Related MCP server: Simple FastMCP Server

Run locally (uv)

uv sync
uv run python app.py

The app uses MCP Streamable HTTP and listens on 0.0.0.0:8080 by default. Its MCP endpoint is /mcp.

Tools

• hello: returns a greeting.

• add: adds two numbers.

• think: waits for the requested non-negative number of seconds.

• thinkSync: waits synchronously and does not advertise MCP task support.

• thinkWithProgress: waits while reporting percentage completion.

think and thinkWithProgress support the preview MCP tasks capability from protocol 2025-11-25. Capable clients can start either tool as a background task, poll its status, and retrieve its final result with io.modelcontextprotocol/related-task metadata. Calls without task augmentation continue to run synchronously. thinkSync provides an explicitly non-task-capable baseline for testing task proxies and synchronous timeout paths.

The default memory:// task backend is intended for this single-process sample. For persistent or horizontally scaled deployments, set FASTMCP_DOCKET_URL=redis://<host>:6379/0 and configure every server and worker to use the same backend.

Direct task client

import asyncio

from fastmcp import Client


async def main() -> None:
    async with Client("http://127.0.0.1:8080/mcp") as client:
        task = await client.call_tool(
            "thinkWithProgress",
            {"seconds": 120},
            task=True,
        )
        print(f"Started task {task.task_id}")
        print(await task.result())


asyncio.run(main())

Microsoft Foundry

Foundry long-running operations are a preview feature. Use a supported model, call the Responses API with background=True, and poll the response until it reaches a terminal state. Foundry recognizes the task reference returned by the MCP server and polls the MCP task instead of keeping one tool request open for the full wait duration.

import time

response = openai.responses.create(
    input="Use thinkWithProgress to wait for 120 seconds.",
    extra_body={"agent_reference": {"name": agent.name, "type": "agent_reference"}},
    background=True,
)

while response.status in {"queued", "in_progress"}:
    time.sleep(2)
    response = openai.responses.retrieve(response.id)

print(response.output_text)

Health check:

curl -sS http://127.0.0.1:8080/health

Docker

Build image:

docker build -t simple-testing-mcp .

Run container:

docker run --rm -p 8080:8080 simple-testing-mcp

Pushes to main publish multi-architecture images to ghcr.io/<owner>/<repository> with latest, main, and commit SHA tags. The workflow can also be run manually from the Actions tab.

Health check:

curl -sS http://127.0.0.1:8080/health