Get detailed website visits and traffic insights like Google Analytics using Fathom Analytics. Monitor real-time data an
Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
Google Search Console
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MCP Science: Easily discover and run scientific research MCP servers from the Path Integral Institute with automated set
BioMCP (Biomedical Database Integration)
BioMCP integrates ClinicalTrials.gov, PubMed, and MyVariant.info for unified biomedical database access with structured,
GitHub Chat
GitHub Chat lets you query, analyze, and explore GitHub repositories with AI-powered insights, understanding codebases f
Google Cloud Platform
Integrate with Google Drive and GCloud Storage via Google Cloud Platform for seamless access to Compute Engine, BigQuery
I recommend Fathom Analytics for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Fathom Analytics is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
We evaluated Fathom Analytics against two servers with overlapping tools; this profile had the clearer scope statement.
Fathom Analytics is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Fathom Analytics is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Fathom Analytics is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
I recommend Fathom Analytics for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We evaluated Fathom Analytics against two servers with overlapping tools; this profile had the clearer scope statement.
Fathom Analytics is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
According to our notes, Fathom Analytics benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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Claude Desktop configuration
{
"mcpServers": {
"fathom-analytics": {
"command": "npx",
"args": [
"-y",
"mcp-fathom-analytics"
],
"env": {
"FATHOM_API_KEY": "your_api_key_here"
}
}
}
}Connects to Fathom Analytics to retrieve website traffic data, visitor stats, and analytics reports through AI assistants.
Fathom Analytics is a community-built MCP server published by mackenly that provides AI assistants with tools and capabilities via the Model Context Protocol. Get detailed website visits and traffic insights like Google Analytics using Fathom Analytics. Monitor real-time data an It is categorized under analytics data.
You can install Fathom Analytics in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
An unofficial Model Context Protocol (MCP) server for accessing Fathom Analytics data through an AI assistant. This implementation uses the @mackenly/fathom-api unofficial SDK to interact with the Fathom Analytics API. Not affiliated, endorsed, or supported by Fathom Analytics. Published to npm as an npx script.
<p float="left"> <a href="https://glama.ai/mcp/servers/56cxbakbc4" width="33%"> <img width="380" height="200" src="https://glama.ai/mcp/servers/56cxbakbc4/badge" alt="Fathom Analytics MCP server" /> </a> <a href="https://mseep.ai/app/mackenly-mcp-fathom-analytics" width="33%"> <img width="200" src="https://mseep.net/pr/mackenly-mcp-fathom-analytics-badge.png" alt="MseeP.ai Security Assessment Badge" /> </a> </p>The MCP server provides the following Fathom Analytics tools:
get-account: Retrieve details about your Fathom Analytics accountlist-sites: List all your Fathom Analytics siteslist-events: List events for a specific siteget-aggregation: Generate aggregated analytics reports with flexible filtering and grouping optionsget-current-visitors: Get real-time data about current site visitorsIf you're using Claude Desktop, you can add the MCP server using the json config (more info). Here's an example:
{
"mcpServers": {
"fathom-analytics": {
"command": "npx",
"args": [
"-y",
"mcp-fathom-analytics"
],
"env": {
"FATHOM_API_KEY": "your_api_key_here"
}
}
}
}
You can find more information about other MCP Clients here: Model Context Protocol Example Clients
The MCP server uses the @mackenly/fathom-api SDK to interface with the Fathom Analytics API endpoints:
https://api.usefathom.com/v1/accounthttps://api.usefathom.com/v1/siteshttps://api.usefathom.com/v1/sites/SITE_ID/eventshttps://api.usefathom.com/v1/aggregationshttps://api.usefathom.com/v1/current_visitorsThe aggregation tool is highly flexible. Here are some example use cases:
{
"entity": "pageview",
"entity_id": "SITE_ID",
"aggregates": "pageviews,uniques,visits",
"date_grouping": "day",
"date_from": "2023-08-01 00:00:00"
}
{
"entity": "pageview",
"entity_id": "SITE_ID",
"aggregates": "pageviews,uniques,avg_duration",
"field_grouping": "pathname",
"sort_by": "pageviews:desc",
"limit": 10
}
{
"entity": "pageview",
"entity_id": "SITE_ID",
"aggregates": "visits",
"field_grouping": "country_code",
"sort_by": "visits:desc"
}
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.