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Deployment

# Testing your FastMCP Server

How to test your FastMCP server.

The best way to ensure a reliable and maintainable FastMCP Server is to test it! The FastMCP Client combined with Pytest provides a simple and powerful way to test your FastMCP servers.

##
​
Prerequisites

Testing FastMCP servers requires `pytest-asyncio` to handle async test functions and fixtures. Install it as a development dependency:

    pip install pytest-asyncio

We recommend configuring pytest to automatically handle async tests by setting the asyncio mode to `auto` in your `pyproject.toml`:

    [tool.pytest.ini_options]
    asyncio_mode = "auto"

This eliminates the need to decorate every async test with `@pytest.mark.asyncio`.

##
​
Testing with Pytest Fixtures

Using Pytest Fixtures, you can wrap your FastMCP Server in a Client instance that makes interacting with your server fast and easy. This is especially useful when building your own MCP Servers and enables a tight development loop by allowing you to avoid using a separate tool like MCP Inspector during development:

    import pytest
    from fastmcp.client import Client
    from fastmcp.client.transports import FastMCPTransport

    from my_project.main import mcp

    @pytest.fixture
    async def main_mcp_client():
        async with Client(transport=mcp) as mcp_client:
            yield mcp_client

    async def test_list_tools(main_mcp_client: Client[FastMCPTransport]):
        list_tools = await main_mcp_client.list_tools()

        assert len(list_tools) == 5

We recommend the inline-snapshot library for asserting complex data structures coming from your MCP Server. This library allows you to write tests that are easy to read and understand, and are also easy to update when the data structure changes.

    from inline_snapshot import snapshot

    async def test_list_tools(main_mcp_client: Client[FastMCPTransport]):
        list_tools = await main_mcp_client.list_tools()

        assert list_tools == snapshot()

Simply run `pytest --inline-snapshot=fix,create` to fill in the `snapshot()` with actual data.
For values that change you can leverage the dirty-equals library to perform flexible equality assertions on dynamic or non-deterministic values.
Using the pytest `parametrize` decorator, you can easily test your tools with a wide variety of inputs.

    import pytest
    from my_project.main import mcp

    from fastmcp.client import Client
    from fastmcp.client.transports import FastMCPTransport
    @pytest.fixture
    async def main_mcp_client():
        async with Client(mcp) as client:
            yield client

    @pytest.mark.parametrize(
        "first_number, second_number, expected",
        [
            (1, 2, 3),
            (2, 3, 5),
            (3, 4, 7),
        ],
    )
    async def test_add(
        first_number: int,
        second_number: int,
        expected: int,
        main_mcp_client: Client[FastMCPTransport],
    ):
        result = await main_mcp_client.call_tool(
            name="add", arguments={"x": first_number, "y": second_number}
        )
        assert result.data is not None
        assert isinstance(result.data, int)
        assert result.data == expected

The FastMCP Repository contains thousands of tests for the FastMCP Client and Server. Everything from connecting to remote MCP servers, to testing tools, resources, and prompts is covered, take a look for inspiration!
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