cerberus-mcp

# cerberus-mcp MCP (Model Context Protocol) server instrumentation for [Cerberus](https://github.com/gpotrock/cerberus) API monitoring. Drop-in replacement for `FastMCP` that captures tool, resource, and prompt call metrics and streams them to the Cerberus analytics pipeline. ## Installation ```bash pip install cerberus-mcp ``` ## Quick Start Replace `FastMCP` with `CerberusMCP` — a single-line change: ```python from cerberus_mcp import CerberusMCP mcp = CerberusMCP( "my-server", cerberus_config={ "token": "your-api-key", "client_id": "your-client-id", "ws_url": "wss://your-cerberus-backend:8765", } ) @mcp.tool() def get_weather(location: str) -> str: """Get weather for a location.""" return f"Sunny in {location}" @mcp.resource("config://settings") def get_settings() -> str: """Return server settings.""" return '{"theme": "dark"}' @mcp.prompt() def summarize(text: str) -> str: """Summarize text.""" return f"Please summarize: {text}" ``` All tool calls, resource reads, and prompt invocations are automatically captured with: - Execution timing (duration_ms) - Sanitized arguments (sensitive values redacted) - Error tracking - Result summaries - MCP client identity (name, version) and session correlation Events are sent asynchronously via WebSocket to the Cerberus event_ingest backend using the same pipeline as `cerberus-django`. ## Configuration | Key | Required | Description | |-----|----------|-------------| | `token` | Yes | API key for Cerberus authentication | | `client_id` | Yes | Client identifier for your MCP server | | `ws_url` | Yes | WebSocket URL of your Cerberus event_ingest server | | `server_name` | No | Override server name in events (defaults to MCP server name) | Set `CERBERUS_DEBUG=true` to enable verbose logging. ## How It Works `CerberusMCP` subclasses `FastMCP` from the MCP Python SDK and wraps the `tool()`, `resource()`, and `prompt()` decorators. Each handler call is …