Matomo MCP Server

Matomo MCP Server

Enables LLMs to directly query a Matomo analytics instance, execute reporting methods, fetch historical trends, report metadata, and dynamically generated chart images through typed MCP tools.

Category
Visit Server

README

Matomo MCP Server

License: MIT TypeScript Node.js Model Context Protocol

Matomo Direct MCP (Model Context Protocol) Server is a robust, lightweight TypeScript implementation that exposes the full power of the Matomo Analytics HTTP Reporting API directly to LLM agents.

Unlike intermediary solutions, this server connects directly to your Matomo instance, allowing clients (like Claude Desktop, Cursor, or custom MCP wrappers) to run reporting queries, fetch historical trend analysis, inspect report metadata, and retrieve dynamically generated graph imagesβ€”all through beautifully typed, auto-documented MCP tools.


πŸš€ Key Features

  • Direct Integration – No proxy databases or external authentication gateways; queries the Matomo HTTP API directly using your token_auth.
  • Full Reporting Coverage – Call any API method from any core or custom plugin.
  • Auto-Validated Inputs – Every tool payload is checked against strict JSON-Schema schemas via the MCP SDK and Zod.
  • Image Generation Support – Directly outputs binary PNG charts (ImageGraph.get) for visualization-capable LLM interfaces.
  • Resilience & Reliability – Configurable request timeouts and robust HTTP retry logic with exponential back-off.
  • Flexible Environments – Fully supports command-line flags, environment variables, and Docker deployment.

πŸ› οΈ Technology Stack


πŸ“ Project Architecture

The Matomo Direct MCP Server operates as a STDIO transport process. It communicates via system standard input/output streams and is fully stateless.

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”             STDIO              β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚                 β”‚  ◄───────────────────────────► β”‚                         β”‚
β”‚   MCP Client    β”‚  (List Tools, Call Tool)       β”‚  Matomo Direct MCP Srv  β”‚
β”‚ (Claude/Cursor) β”‚  ────────────────────────────► β”‚  (TypeScript Process)   β”‚
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜                                β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
                                                               β”‚
                                                       HTTPS Fetch API
                                                       (token_auth, JSON)
                                                               β”‚
                                                               β–Ό
                                                   β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
                                                   β”‚   Matomo Analytics      β”‚
                                                   β”‚   HTTP Reporting API    β”‚
                                                   β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

When started, the server:

  1. Parses & Validates Configuration: Parses CLI flags or environment variables to find the MATOMO_HOST and MATOMO_TOKEN_AUTH.
  2. Verifies Connectivity: Performs a non-blocking startup check against API.getMatomoVersion to ensure the host is reachable.
  3. Exposes Typed Tools: Publishes structured JSON-schemas describing all report actions to the client.
  4. Handles Requests: Receives tool invocations, dynamically builds requests (serializing parameters and authentication tokens), executes HTTP queries, detects content-types (JSON, XML, TSV, CSV, PNG), and formats clean, structured outputs back to the agent.

πŸ“¦ Project Structure

mcp-matomo/
β”œβ”€β”€ src/
β”‚   β”œβ”€β”€ index.ts      # Standalone CLI entrypoint, configuration parsing, and startup
β”‚   └── server.ts     # Core MCP server definition, API client, and tool handlers
β”œβ”€β”€ dist/             # Compiled production JavaScript files (generated via tsc)
β”œβ”€β”€ package.json      # Dependencies, compilation scripts, and metadata
β”œβ”€β”€ tsconfig.json     # Strict TypeScript compiler options
β”œβ”€β”€ .gitignore        # Comprehensive secrets & artifact ignore rules
└── README.md         # Documentation (this file)

πŸš₯ Getting Started

Prerequisites

  • Node.js >= 22.0.0
  • npm >= 10.0.0
  • A running Matomo Analytics instance with an API token (token_auth).

Installation

  1. Clone the repository to your local machine:

    git clone https://github.com/alexgenovese/matomo-mcp.git
    cd matomo-mcp
    
  2. Install development and runtime dependencies:

    npm ci
    

βš™οΈ Configuration

The server can be configured seamlessly using either Command Line Arguments or Environment Variables. CLI flags take priority over environment variables.

CLI Argument Environment Variable Default Description
--matomo-host=URL MATOMO_HOST Required Base URL of your Matomo instance (e.g., https://analytics.yourcompany.com/).
--matomo-token=TOKEN MATOMO_TOKEN_AUTH Required Your Matomo secret API token (token_auth).
--timeout=MS REQUEST_TIMEOUT 30000 HTTP request timeout in milliseconds.
--retry=COUNT RETRY_COUNT 3 Maximum HTTP request retries.
--retry-delay=MS RETRY_DELAY 1000 Initial retry delay in ms. Multiplied exponentially on consecutive failures.
--format=FORMAT MATOMO_DEFAULT_FORMAT json Default response format for reporting queries (e.g., json, xml).

πŸƒ Running the Server

1. Local Development (with Hot Reloading)

Run the server directly from TypeScript source code using tsx:

npm run dev -- --matomo-host=https://your-matomo-url.com --matomo-token=your_token_auth

2. Production Build & Execution

Compile the TypeScript project to production-ready ES modules, then execute using Node:

# Compile TS to JS in /dist
npm run build

# Run stand-alone server
node dist/index.js --matomo-host=https://your-matomo-url.com --matomo-token=your_token_auth

3. Running with Docker

You can containerize and run the server inside a Docker environment:

# Build the Docker image
docker build -t matomo-mcp .

# Run the container
docker run -i --rm -e MATOMO_HOST="https://your-matomo-url.com" -e MATOMO_TOKEN_AUTH="your_token_auth" matomo-mcp

πŸ› οΈ MCP Tools Overview

The server exposes six highly focused, dynamically parameterized tools:

1. matomo_call

Generic, escape-hatch endpoint to run any Matomo HTTP API reporting method.

  • Required Arguments:
    • method (string): The Module.action signature (e.g., VisitsSummary.get or UsersManager.getUsers).
  • Optional Arguments:
    • params (object): Key-value pairs representing request arguments.
    • format (enum): Output serialization format (json, xml, csv, tsv, html, rss, original, png).

2. matomo_list_report_metadata

Fetch the complete metadata suite of compatible reports for a site.

  • Required Arguments:
    • idSite (integer): ID of the Matomo website.
  • Optional Arguments:
    • period, date, language, showSubtableReports, hideMetricsDoc.

3. matomo_get_metadata

Query granular metadata schemas, documentation, and specific column dimensions of a single report action.

  • Required Arguments:
    • idSite (integer), apiModule (string), apiAction (string).

4. matomo_get_processed_report

Retrieve high-level processed metrics, calculations, and tables complete with arithmetic.

  • Required Arguments:
    • idSite (integer), apiModule (string), apiAction (string).
  • Optional Arguments:
    • segment (segment filter string), flat (boolean), expanded (boolean), filter_limit (integer).

5. matomo_get_row_evolution

Analyze historical trend lines for a specific report row label over time.

  • Required Arguments:
    • idSite (integer), apiModule (string), apiAction (string), label (string).

6. matomo_get_image_graph

Acquire raw PNG chart visualizations directly generated by Matomo's Graph Engine.

  • Required Arguments:
    • idSite (integer), apiModule (string), apiAction (string).
  • Optional Arguments:
    • graphType (evolution, horizontalBar, verticalBar, pie), width, height, columns.

πŸ”Œ Integration Guides

Claude Desktop Integration

To register this server with your local Claude Desktop app, edit your configuration file (usually located at ~/Library/Application Support/Claude/claude_desktop_config.json on macOS, or %APPDATA%\Claude\claude_desktop_config.json on Windows) and add the following entry:

{
  "mcpServers": {
    "matomo-direct-mcp": {
      "command": "node",
      "args": [
        "/Users/alexgenovese/Documents/GitHub/mcp/mcp-matomo/dist/index.js",
        "--matomo-host=https://your-matomo-instance.com",
        "--matomo-token=YOUR_MATOMO_TOKEN_AUTH"
      ]
    }
  }
}

Note: Ensure you have compiled the server beforehand by running npm run build.


πŸ’» Development Workflow

Coding Standards

We enforce highly clean, structured, and modern development standards:

  • Strict Types: Explicit typings everywhere; any is restricted only to generic API parsing.
  • Modular ES Imports: Node.js ES Modules are strictly enforced. Relative file imports must include the .js extension (e.g. import { Server } from "./server.js").
  • Robust Error Handling: Network failures are monitored and retried using structured back-offs, while standard error objects are printed to standard error (console.error) so as not to corrupt the STDIO transport on standard output.

Linting

Validate codebase health and alignment to guidelines:

npm run lint

🀝 Contributing

Contributions are welcome! Please follow these simple steps to contribute:

  1. Fork the repository and create your feature branch (git checkout -b feature/amazing-feature).
  2. Verify changes build perfectly and conform to standard formatting guidelines.
  3. Open a Pull Request detailing the purpose and scope of your modifications.

πŸ“„ License

This project is licensed under the MIT License - see the package.json file for licensing declarations.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured