aiohttp-tiny-mcp

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An MCP server and client library for aiohttp, designed for remote MCP over HTTP across multiple processes and servers.

Use it to expose your application's operations and data to assistants: search a catalog, read a document, or request a deployment. You declare async Python handlers and Pydantic argument models. The library publishes tool, resource, and prompt descriptions, validates calls, and handles MCP messages and streams. It supports five protocol revisions from the same handler declarations, and is optimized for low-overhead HTTP and stdio operation. See performance for reproducible measurements and methodology.

Shared state (optional)

Registry uses in-memory sessions and events by default, which is suitable for tests and one process. For multiple workers, give every worker the same SessionStore and Hub: SQLite for workers on one machine, Redis or PostgreSQL across machines. The backend owns persistence; handlers use Exchange (ex.session, ex.ask, progress) without knowing which backend is in use.

For a local multi-process setup:

from aiohttp import web

from aiohttp_tiny_mcp import Registry
from aiohttp_tiny_mcp.sqlite import SqliteHub, SqliteSessionStore, SqliteStorage

storage = SqliteStorage("mcp.sqlite")
registry = Registry(
    "service", "1.0", hub=SqliteHub(storage), session_store=SqliteSessionStore(storage)
)

app = web.Application()
# Open the file for the application's lifetime and sweep expired rows.
app.cleanup_ctx.append(storage.cleanup_ctx)

For Redis/PostgreSQL setup, backend parameters, cleanup, and deployment constraints, see stores and hubs.

Start a server

Python 3.10+ is required. Runtime dependencies are aiohttp and pydantic.

pip install aiohttp-tiny-mcp

For a first runnable server and client, follow the quickstart. The example below adds a resource and a tool that asks for confirmation. Save it as server.py. The deployment result is illustrative; replace it with your application's operation.

from aiohttp import web
from pydantic import BaseModel

from aiohttp_tiny_mcp import (
    Endpoint,
    Exchange,
    Registry,
    elicit,
)

registry = Registry("demo", "0.1.0")


class Nothing(BaseModel):
    pass


class Deploy(BaseModel):
    service: str


@registry.resource("config://app", mime_type="application/json")
async def config(args: Nothing) -> dict:
    """Application configuration."""
    return {"debug": False}


@registry.tool
async def deploy(args: Deploy, ex: Exchange) -> str:
    """Deploy a service, once somebody agrees to it."""
    agreed = await ex.ask("confirm", elicit(f"Deploy {args.service}?"))
    if not agreed.accepted:
        return f"stopped at {agreed.action}"
    return f"deployed {args.service}"


app = Endpoint(registry).app("/mcp")

if __name__ == "__main__":
    web.run_app(app, host="127.0.0.1", port=8080)

Run it locally:

python server.py

To try it without a client, mount the console beside the endpoint:

from aiohttp_tiny_mcp.console import Console

Console("/mcp", title="Demo").setup(app, "/console")

Open http://127.0.0.1:8080/console. It speaks the protocol itself on any of the five revisions, builds a form from each tool's schema, answers the questions a handler asks, and shows every message either way. Three files from this package, no build step and no second process.

An MCP host that supports Streamable HTTP can connect to http://127.0.0.1:8080/mcp. In an existing aiohttp service, use Endpoint(registry).setup(app, "/mcp"). For a local subprocess transport, run_stdio(registry) serves the same declarations.

The Deploy model becomes the tool's input schema; the function name and docstring become its name and description. ex: Exchange is supplied by the library, so the caller only supplies service. ex.ask requests a decision from the client. Put irreversible work after the final question: some revisions restart the handler when the answer arrives. Python locals are not persisted automatically. See Asking the user.

Call it from Python

The bundled Client is useful for integration tests or an application that connects to MCP servers. The following runs inside an async function with url set to your endpoint URL. Its callback automatically accepts the question; in an interactive application, collect the user's answer there.

from aiohttp_tiny_mcp import Client, elicit_accept
from aiohttp_tiny_mcp.protocol.selection import AdapterSet


async def answer(request):
    return elicit_accept({"ok": True})


adapter = AdapterSet.default().by_version["2025-06-18"]
async with Client(url, adapter, on_ask=answer, log_level="info") as client:
    await client.initialize()
    result = await client.call_tool("deploy", {"service": "web"})

    async for change in client.listen(resources=["config://app"]):
        print(change["params"]["uri"])
        break

The subscription loop waits for a resource-change event. The server snippet above does not publish changes; see Notifications for that part, or omit the loop when testing only the tool call. StdioClient provides the corresponding client over a subprocess's stdin/stdout.

Performance

The project includes reproducible HTTP and stdio benchmarks against the official SDK. Results depend on Python, hardware, and protocol revision; see the benchmark methodology and full results instead of treating a README number as a guarantee.

Documentation

Start with the documentation overview, then follow:

1. Tools, resources, and prompts: what to expose and what the client sees.
2. Quickstart: a complete server, launch command, and client call.
3. How the server fits together: a conversation across two workers and each object's lifetime.
4. Using Exchange: request context, progress, questions, and state.
5. Authentication: bearer-token verification and OAuth resource metadata.
6. Stores and hubs: shared backend contracts and deployment requirements.

The server supports 2026-07-28, 2025-11-25, 2025-06-18, 2025-03-26 and 2024-11-05. Delivery mechanisms and client support differ; see the compatibility table and implementation coverage.

Documentation examples are checked by the test suite. From a source checkout:

uv run pytest docs README.md
uv run --group docs sphinx-build -W -b html docs docs/_build