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Mcpcat Python SDK

MCPcat is an analytics platform for MCP server owners 🐱.

72Good

Scored 2 days ago · breakdown

About Mcpcat Python SDK

Mcpcat Python SDK is an MCP server published by MCPCat in the Developer Tools category: mCPcat is an analytics platform for MCP server owners 🐱. It has been installed 0 times through Conduid.

The repository has 46 stars and 7 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx mcpcat-python-sdk

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

  • ·README presentNot checked yet.
  • ·License declaredNot checked yet.
  • ·Tests presentNot checked yet.
  • ·Dependencies pinnedNot checked yet.
  • ·No dynamic code executionNot checked yet.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

v2.1.0AgentCat v2.1.0 — sturdier session handles: IDs issued first, structured mcp_session status · 31 Aug 2026AgentCat v2.1.0 makes explicit session handles sturdier and easier for agents to consume. There are no `track()` API changes — the delta is in the wire contract between your server and the agent. What's new IDs are issued at the start of…
v2.0.2AgentCat v2.0.2 — event-level redact_event hook · 8 Aug 2026AgentCat now supports an event-level `redact_event` hook, matching the `redactEvent`/`RedactEvent` hooks already available in the TypeScript and Go SDKs — plus a round of hardening on top after an adversarial review of the new surface.…
v2.0.1AgentCat v2.0.1 — FastMCP Code Mode support · 6 Aug 2026AgentCat now fully supports servers built on [FastMCP Code Mode](https://gofastmcp.com/servers/code-mode) — and, more generally, any server that calls itself mid-request: catalog meta-tools fetching the hidden catalog, sandboxes chaining…
v2.0.0AgentCat v2.0.0 — explicit handles for sessionless MCP, and MCP Python SDK v2 support · 5 Aug 2026AgentCat v2 rebuilds task correlation for the sessionless MCP era — and adds full support for MCP Python SDK v2. Why v2 The [MCP 2026-07-28 specification](https://blog.modelcontextprotocol.io/posts/2026-07-28/) removed protocol-level…
v0.1.15v0.1.15 — final mcpcat release (renamed to agentcat) · 4 Jul 2026MCPcat is now AgentCat** 🐱 — same team, same product, new name. This is the **final release of the `mcpcat` package**. It has been renamed to [`agentcat`](https://pypi.org/project/agentcat/) (`pip install agentcat`, starting fresh at…

README

[!NOTE] Looking for the TypeScript SDK? Check it out here mcpcat-typescript.

MCPcat is an analytics platform for MCP server owners 🐱. It captures user intentions and behavior patterns to help you understand what AI users actually need from your tools — eliminating guesswork and accelerating product development all with one-line of code.

This SDK also provides a free and simple way to forward telemetry like logs, traces, and errors to any Open Telemetry collector or popular tools like Datadog and Sentry.

# Basic installation (includes official MCP SDK)
pip install mcpcat

# With Jlowin's/Prefect's FastMCP support
pip install "mcpcat[community]"

To learn more about us, check us out here

Why use MCPcat? 🤔

MCPcat helps developers and product owners build, improve, and monitor their MCP servers by capturing user analytics and tracing tool calls.

Use MCPcat for:

  • User session replay 🎬. Follow alongside your users to understand why they're using your MCP servers, what functionality you're missing, and what clients they're coming from.
  • Trace debugging 🔍. See where your users are getting stuck, track and find when LLMs get confused by your API, and debug sessions across all deployments of your MCP server.
  • Existing platform support 📊. Get logging and tracing out of the box for your existing observability platforms (OpenTelemetry, Datadog, Sentry) — eliminating the tedious work of implementing telemetry yourself.

Getting Started

To get started with MCPcat, first create an account and obtain your project ID by signing up at mcpcat.io. For detailed setup instructions visit our documentation.

Once you have your project ID, integrate MCPcat into your MCP server:

import mcpcat
from mcp.server import FastMCP

server = FastMCP(name="echo-mcp", version="1.0.0")

mcpcat.track(server, "proj_0000000")

Identifying users

You can identify your user sessions with a simple callback MCPcat exposes, called identify.

def identify_user(request, extra):
    user = myapi.get_user(request.params.arguments.token)
    return UserIdentity(
            user_id=user.id,
            user_name=user.name,
            user_data={
                "favorite_color": user.favorite_color,
            },
    )

mcpcat.track(server, "proj_0000000", MCPCatOptions(identify=identify_user))

Redacting sensitive data

MCPcat redacts all data sent to its servers and encrypts at rest, but for additional security, it offers a hook to do your own redaction on all text data returned back to our servers.

# Sync version
def redact_sync(text):
    return custom_redact(text)

mcpcat.track(server, "proj_0000000", redact_sensitive_information=redact_sync)

Forwarding data to existing observability platforms

MCPcat seamlessly integrates with your existing observability stack, providing automatic logging and tracing without the tedious setup typically required. Export telemetry data to multiple platforms simultaneously:

from mcpcat import MCPCatOptions, ExporterConfig

mcpcat.track(
    server, 
    "proj_0000000", # Or None if you just want to use the SDK to forward telemetry
    MCPCatOptions(
        exporters={
            # OpenTelemetry - works with Jaeger, Tempo, New Relic, etc.
            "otlp": ExporterConfig(
                type="otlp",
                endpoint="http://localhost:4318/v1/traces"
            ),
            # Datadog
            "datadog": ExporterConfig(
                type="datadog",
                api_key=os.getenv("DD_API_KEY"),
                site="datadoghq.com",
                service="my-mcp-server"
            ),
            # Sentry
            "sentry": ExporterConfig(
                type="sentry",
                dsn=os.getenv("SENTRY_DSN"),
                environment="production"
            )
        }
    )
)

Learn more about our free and open source telemetry integrations.

Free for open source

MCPcat is free for qualified open source projects. We believe in supporting the ecosystem that makes MCP possible. If you maintain an open source MCP server, you can access our full analytics platform at no cost.

How to apply: Email hi@mcpcat.io with your repository link

Already using MCPcat? We'll upgrade your account immediately.

Community Cats 🐱

Meet the cats behind MCPcat! Add your cat to our community by submitting a PR with your cat's photo in the docs/cats/ directory.

Want to add your cat? Create a PR adding your cat's photo to docs/cats/ and update this section!

README mirrored from the source repository 2 days ago. The original is authoritative.

Questions

About Mcpcat Python SDK

How do I install Mcpcat Python SDK?

Run npx mcpcat-python-sdk, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Mcpcat Python SDK safe to use with an AI agent?

Its trust score is 72 out of 100 (good). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Mcpcat Python SDK still maintained?

Yes — the latest release is v2.1.0 (31 Aug 2026), and the last commit was 6 months ago. The repository has 46 stars and 0 open issues.