@mj-kiwi/matomo-mcp-server v0.1.3
Matomo MCP Server
⚠️ This package is currently under construction and may not be fully functional. ⚠️
This package implements a Model Context Protocol (MCP) server that acts as a bridge between an AI agent (like a large language model) and a Matomo analytics instance. It exposes Matomo Reporting API functionalities as MCP tools.
Configuration
The server requires connection details for your Matomo instance. Configure these using environment variables:
MATOMO_URL: The base URL of your Matomo instance (e.g.,https://your-matomo.example.com).MATOMO_AUTH_TOKEN: Your Matomo API authentication token.MATOMO_DEFAULT_SITE_ID: (Optional) The default Matomo site ID to use if not specified in a tool call. Defaults to1.
If these variables are not set, the server will use placeholder values and print a warning.
Running the Server
You can run the server directly using Node.js:
node build/index.jsOr, if you have configured it as an executable in package.json:
matomo-mcp-serverThe server communicates over standard input/output (stdio).
Available Tools
Module Implementation Status
Below is a checklist showing the implementation status of all Matomo API modules in the MCP server:
- SitesManager
- AbTesting
- Actions
- ActivityLog
- AdvertisingConversionExport
- Annotations
- Api
- ConnectAccounts
- Contents
- CoreAdminHome
- CrashAnalytics
- CustomAlerts
- CustomDimensions
- CustomJsTracker
- CustomReports
- CustomVariables
- Dashboard
- DevicePlugins
- DevicesDetection
- Events
- Feedback
- FormAnalytics
- Funnels
- Goals
- HeatmapSessionRecording
- ImageGraph
- Insights
- LanguagesManager
- Live
- Login
- MarketingCampaignsReporting
- MediaAnalytics
- MobileMessaging
- MultiChannelConversionAttribution
- MultiSites
- Overlay
- PagePerformance
- PrivacyManager
- Referrers
- Resolution
- RollUpReporting
- ScheduledReports
- SearchEngineKeywordsPerformance
- SegmentEditor
- Seo
- TagManager
- Tour
- Transitions
- TwoFactorAuth
- UserCountry
- UserId
- UserLanguage
- UsersFlow
- UsersManager
- VisitFrequency
- VisitTime
- VisitorInterest
- VisitsSummary
Overall progress: 4 modules implemented out of 47 total modules (8.5% complete).