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dishka-fastmcp

CI Coverage PyPI Downloads Python versions License: MIT llms.txt Documentation Context7 skills.sh

dishka IoC container integration for FastMCP. Declare dependencies as FromDishka[Service] in MCP tools, resources and prompts and let dishka resolve them per request — with real scopes, finalization and modular providers, sharing one container with the rest of your application.

from dishka import Provider, Scope, make_async_container, provide
from fastmcp import FastMCP

from dishka_fastmcp import FromDishka, dishka_lifespan, inject, setup_dishka


class Catalog:
    _prices: dict[str, int] = {'book': 12, 'pen': 2}

    def price(self, item: str) -> int:
        return self._prices.get(item, 0)


class AppProvider(Provider):
    catalog = provide(Catalog, scope=Scope.REQUEST)


container = make_async_container(AppProvider())
mcp = FastMCP('shop', lifespan=dishka_lifespan(container))
setup_dishka(container, mcp)


@mcp.tool
@inject
async def get_price(item: str, catalog: FromDishka[Catalog]) -> int:
    return catalog.price(item)


if __name__ == '__main__':
    mcp.run()

The client sees a tool that takes only item — catalog is injected at call time and never appears in the schema.

Install

uv add dishka-fastmcp        # or: pip install dishka-fastmcp

Requires Python 3.11+, dishka>=1.10.1, fastmcp>=4.0.0,<5 and mcp>=2.0.0,<3. Servers still on FastMCP 3.x should stay on dishka-fastmcp 2.0.x.

With a coding agent

The repository ships an Agent Skill that walks a coding agent through adding dishka-fastmcp to a FastMCP server: the container and lifespan, decorator order, sync and async handlers, mounted routers, the request-wide scope, and tests that assert the tool schema. It installs into Claude Code, Cursor, Codex, GitHub Copilot, Gemini CLI and the other agents that read the open skills format:

npx skills add bagowix/dishka-fastmcp

Agents that read documentation directly can use llms.txt or Context7.

How it works

Registration time and execution time are separate concerns:

  • @inject sits below the FastMCP decorator. @mcp.tool builds the JSON schema from the function signature. @inject rewrites that signature first, stripping every FromDishka parameter, so the schema the LLM sees contains only the real client-facing arguments. Order matters — @inject must be the inner decorator. Placed above, it fails at import: FastMCP has registered the bare function by then, and the client would fill in the dependency itself.
  • setup_dishka associates the root container with the FastMCP application. @inject selects that container from the application handling the current operation, then opens and finalizes Scope.REQUEST around the handler, or shares the scope DishkaMiddleware opened for the whole request. For a sync handler, dependency setup, use, and cleanup all happen in its worker thread.
  • Mounted routers use the serving server's container. dishka_lifespan puts the container into the lifespan state of the server you serve, and routers mounted into it at any depth read it from there during MCP requests. A router mounted into several servers uses the container of the one serving the request. A router with its own setup_dishka keeps its own container, and so does one with its own dishka_lifespan if it is mounted before the server starts. Routers below such a router still take the serving root's. Direct server.call_tool() calls outside an MCP request and servers behind create_proxy are not covered; see Mounted servers.

Scopes

Scope Boundary Lifetime
Scope.APP The whole server Owned by the root container; dishka_lifespan closes it on shutdown, or its owner does (see below)
Scope.SESSION One MCP connection Opt-in: opened by DishkaMiddleware(session_scope=True), finalized when the connection closes
Scope.REQUEST One tool call / resource read / prompt render Opened and finalized by @inject around the handler, or by DishkaMiddleware around the whole MCP request

Scope.SESSION follows the MCP connection, so it spans several requests only where a connection does: 2025 handshake clients over stdio, stateful Streamable HTTP, SSE or an in-memory Client(server, mode='legacy'). The 2026-07-28 protocol, which FastMCP 4's own Client speaks by default, and stateless HTTP build a fresh connection for every request, and there a SESSION dependency lives for one request. See Session scope.

Closing the container

setup_dishka does not own the server lifecycle, so it does not close the root container. dishka_lifespan(container) — used in the example above — closes it (async or sync) and removes its application registration when the server stops, finalizing every Scope.APP provider. If you already have a lifespan, compose it with dishka_lifespan using FastMCP's combine_lifespans, or through | when it is a FastMCP @lifespan function. For multiple FastMCP servers hosted by one ASGI application, combine each mcp.http_app().lifespan; see Lifecycle and scopes.

If the same container also serves FastAPI, FastStream, a worker or a test session, the MCP server must not close it while they still use it. List mcp.http_app().lifespan first in combine_lifespans, or pass dishka_lifespan(container, finalize_container=False) and close the container where it is owned; see Sharing the container.

FastMCP may execute regular sync handlers on different worker threads. Consequently, Scope.APP dependencies in a sync container must be thread-safe and their cleanup must not require the thread that created them. Put thread-affine resources such as sqlite3.Connection in Scope.REQUEST, where dishka-fastmcp guarantees creation, use and finalization in one worker thread.

Background tasks

FastMCP's task=True handlers are not supported. In FastMCP 4 they come from the optional fastmcp-tasks extension and run in a task worker, detached from the request that queued them and possibly in another process. @inject detects the worker and raises DishkaFastMCPError there. Keep FromDishka handlers request-bound; if you need background work, resolve dependencies inside the request and pass plain values to the task.

Resources and prompts

@inject works the same on resources and prompts — dependencies are resolved per operation:

@mcp.resource('users://{user_id}')
@inject
async def user(user_id: str, repo: FromDishka[UserRepo]) -> dict:
    return await repo.get(user_id)


@mcp.prompt
@inject
async def summarize(text: str, summarizer: FromDishka[Summarizer]) -> str:
    return await summarizer.run(text)

Sync handlers

FastMCP runs regular sync handlers in a worker thread. Use a sync container (make_container) for them; the REQUEST scope is created and finalized in that same thread:

from dishka import make_container

container = make_container(AppProvider())
mcp = FastMCP('sync', lifespan=dishka_lifespan(container))
setup_dishka(container, mcp)


@mcp.tool
@inject
def get_price_sync(item: str, catalog: FromDishka[Catalog]) -> int:
    return catalog.price(item)

Async handlers need an async container (make_async_container); mixing the two raises a clear error.

Return values

An ordinary def or async def handler must return its completed value. Returning an awaitable, generator, or async generator is rejected: FastMCP would run that work after the handler returns, when its REQUEST scope may already be finalized. FastMCP tool handlers defined directly as sync or async generator functions are supported; their scope stays open for the whole iteration.

Accessing FastMCP objects

Add FastMCPProvider to expose the current request's FastMCP objects to your dependencies via dishka's from_context:

from fastmcp import Context

from dishka_fastmcp import FastMCPProvider

container = make_async_container(AppProvider(), FastMCPProvider())


@mcp.tool
@inject
async def request_id(ctx: FromDishka[Context]) -> str:
    return ctx.request_id

FastMCPProvider also exposes the active FastMCP server.

Request scope for the whole request

@inject scopes one handler call. To give dynamic component providers, FunctionTool callables and middleware the same REQUEST dependencies, add DishkaMiddleware first in the middleware list and resolve through get_request_container():

from dishka_fastmcp import DishkaMiddleware, get_request_container

mcp = FastMCP(
    'shop',
    lifespan=dishka_lifespan(container),
    middleware=[DishkaMiddleware()],
)


async def current_user() -> User:
    return await get_request_container().get(User)

Every request then gets one scope, list requests included, shared by async @inject handlers and finalized once before the response goes out. It needs an AsyncContainer. Without the middleware nothing changes; see Request scope for the whole MCP request for the rules.

How this compares

vs fastmcp.dependencies.Depends

FastMCP's own Depends injects a per-call value and hides it from the schema — enough for simple cases. dishka adds what Depends does not have: scopes with finalization, modular providers, and one container shared with the rest of your app (the same graph that feeds your FastAPI or FastStream code can feed your MCP server). Reach for dishka-fastmcp when your MCP server is part of a larger dishka application, or when your dependencies own resources that must be set up and torn down per request.

fastmcp-dishka

fastmcp-dishka is an earlier, independent package with a similar name and the same goal. The two are not interchangeable: install one, and import dishka_fastmcp for this one. When moving over, add dishka_lifespan(container) to the server and check its Scope.SESSION providers: here a SESSION dependency is rebuilt for every request unless you add DishkaMiddleware(session_scope=True), and even then it spans requests only on 2025 handshake connections.

License

MIT — see LICENSE.

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