mcpspan for Python

Analytics for MCP servers. Find out which of your tools get called, by which client, how long they take, and which ones fail.

Your own logs tell you a tool ran. This tells you whether it was Claude, Cursor, or something you have not heard of, how that call compares to the other nine hundred, and whether the failures are your tool breaking or your tool politely saying no.

Install

pip install mcpspan

Needs Python 3.10 or newer. No dependencies. Works with the official MCP SDK, mcp 1.30+ (FastMCP) and 2.2+ (MCPServer), and with FastMCP 4+ (the fastmcp package).

Use

One line, anywhere before the server starts:

import os

import mcpspan
from mcp.server.fastmcp import FastMCP

mcp = FastMCP("flights")


@mcp.tool()
def search_flights(destination: str) -> str:
    return f"Found 3 flights to {destination}"


mcpspan.instrument(
    mcp,
    api_key=os.environ.get("MCPSPAN_API_KEY"),
    endpoint="http://localhost:6271",  # your mcpspan installation
)

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

Every tool on the server is measured, whether it was registered before that line or after. Nothing about how you write tools changes: the schema the server builds from your function is untouched, and your tool returns and raises exactly what it did before.

The same line works on v2 of the MCP SDK and on FastMCP:

from mcp.server.mcpserver import MCPServer

mcp = MCPServer("flights")
mcpspan.instrument(mcp)

from fastmcp import FastMCP

mcp = FastMCP("flights")
mcpspan.instrument(mcp)

With no api_key given, it is read from MCPSPAN_API_KEY.

Sessions and clients

Calls are grouped into sessions when there is a connection to group them by: a stdio process, or an HTTP transport that hands out session IDs. A stateless HTTP endpoint, and every endpoint on the 2026-07-28 protocol, which dropped sessions, records calls without one.

The client is read from the call itself on 2026-07-28, where each request names its client, and from the handshake on 2025-11-25. A stateless 2025-11-25 HTTP endpoint has no handshake to read, so its calls are recorded with an unknown client rather than a guessed one.

A tool that asks the client for more before it can finish is one call however many round trips that takes. The interim answer asking for input is not counted; the one that ends the call is.

Without a key

If there is no key, nothing is collected and nothing is sent, and no thread is started. Wrapped tools return before reading the clock. That makes it safe to leave in place in tests, in CI, and in a fork somebody is only reading.

One tool at a time

If your server is not one of the above, or you want to pick tools by hand:

import mcpspan

mcpspan.configure()  # reads MCPSPAN_API_KEY and MCPSPAN_ENDPOINT


@mcpspan.track("search_flights")
async def search_flights(destination: str) -> str:
    return f"Flights to {destination}"

track keeps the function's signature, name and docstring, so a server builds the same schema from it. A function tracked by hand and then registered on an instrumented server is counted once.

Leaving a tool out

@mcp.tool()
@mcpspan.exclude
def health_check() -> str:
    return "ok"

For tools called by machinery rather than by an agent. A health check polled every few seconds outnumbers everything a person does and drags the whole server's error rate and response time towards its own. Put exclude below the server's decorator, so the server registers the marked function.

It takes no tool name on purpose: a name written twice can drift during a rename, and the exclusion would quietly stop applying.

Resources and prompts

Reads of your resources and gets of your prompts are measured too, with nothing to add: each is one event, in the same session and from the same client as the tool calls around it, and the dashboard shows them in a card of their own and in each session's timeline. Listings are not recorded.

A resource at a fixed address is named by that address. One read through a template is named by the template, trips://{id}, never by the address the client asked for, which can carry a user's data; the template's variables are its parameters, by name only. A read of an address the server has nothing for is named by its scheme alone, db://. A prompt is named by its name, and its arguments are its parameters, as a tool's are.

On the official MCP SDK and on FastMCP alike.

Versions

Every call carries the version of the server that answered it, so the dashboard marks where each release began and compares it with the one before. There is nothing to add: it is the version the server gives itself, MCPServer("flights", version="1.4.0") on v2 of the MCP SDK or FastMCP("flights", version="1.4.0"). v1's FastMCP takes no version, so there, or to record a commit or a deploy instead, set server_version (or MCPSPAN_SERVER_VERSION). The client's version is recorded beside its name.

Shutting down

Queued events are delivered as the interpreter exits, so most servers need nothing here. If yours has its own shutdown path and you want to be explicit:

mcpspan.shutdown()

It blocks for as long as that last delivery takes, a few seconds at most. A process killed outright (kill -9, a container stopped without notice) runs nothing after that, and the last few seconds of calls go with it.

Forked workers, as under gunicorn, keep collecting: each starts its own delivery on its first call.

Two kinds of failure

MCP asks tools to report their own errors inside the result, with isError set, so the model can see what went wrong. A raised exception is the deviation from that, and usually means the tool broke.

Both are recorded, and each event says which happened, with the exception's class name for the second: "no flights found" is a tool working as written, while a KeyError is something to fix. On FastMCP, a ToolError you raise on purpose is recorded as ToolError; anything else your tool raises is recorded as itself, not as the error FastMCP wraps it in.

And two that never reach your tool

Calls the server refuses on its own are recorded too: arguments that fail validation, and names it has no tool for. Both reach the model as error results. Bad arguments are the commonest way an agent fails, so leaving them out would make a server look healthier than it is to the agents using it.

A refused call carries no message, because the validation text can quote back what the agent sent. With capture_parameter_names on, it carries the names and types of the arguments instead, which is what shows the agent wrote dest where the schema says destination. Tools passed through exclude stay out of this as well.

Privacy

Parameter values never leave your process. Not by default, not in any mode, not in debug.

What is collected: the tool name, how long it took, whether it succeeded, the error type and a truncated message when it did not, which client called, and the SDK version. For a resource or a prompt, the same, under the name it was registered with: never the address a client read, only its template or, for an address the server does not have, its scheme.

Optionally, parameter names and types:

mcpspan.instrument(mcp, capture_parameter_names=True)

That records {"destination": "string", "passengers": "number"}, in JSON's vocabulary, as the client sent them. Knowing search_flights is always called with destination and never with departure_date tells you your tool description is not landing. Knowing which destination tells you nothing you needed, and puts your users' data somewhere it does not belong.

Self-hosting

Point it at your own installation:

mcpspan.instrument(mcp, endpoint="https://mcpspan.example.com")

Or set MCPSPAN_ENDPOINT. There is no default: events go only where you point them. With a key and no endpoint, nothing is collected, and the SDK says so once on standard error.

When it starts with a key, the SDK sends one empty batch to say it is there. That is how the dashboard's Status page tells a server nobody has used yet from one pointed at the wrong address, and how a wrong key is reported when your server starts rather than at its first tool call.

It will not break your server

• Delivery happens on a background thread of its own, whether your server is synchronous, on asyncio or on trio. A tool call returns without waiting on the network, and the thread never keeps a process alive.
• A failure to send is never raised into your code. Retryable failures wait and try again with a widening gap; a refused key switches collection off and says so once on standard error.
• The queue is bounded. An unreachable endpoint cannot grow it until your process runs out of memory.
• Nothing is ever written to standard output, which carries the MCP protocol on a stdio server. Diagnostics go to standard error.
• configure, instrument and shutdown never raise. A mistyped option falls back to its default rather than stopping your server from starting.

Options

Given to instrument or configure.

Calling configure or instrument again with the same settings changes nothing, so a server built per request can pass them every time.

Developing

uv sync --group mcp2        # or mcp1, or fastmcp: the MCP SDK the tests run against
uv run --group mcp2 pytest
uv run --group mcp2 mypy
uv run ruff check && uv run ruff format --check

The SDK follows the contract every mcpspan SDK follows, checked by the suite in conformance/.

Licence

MIT.