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MCPcat is an analytics platform for MCP server owners 🐱.
[!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
MCPcat helps developers and product owners build, improve, and monitor their MCP servers by capturing user analytics and tracing tool calls.
Use MCPcat for:
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")
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))
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)
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.
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
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