Fathom Analytics▌
by mackenly
Get detailed website visits and traffic insights like Google Analytics using Fathom Analytics. Monitor real-time data an
Integrates with Fathom Analytics to retrieve account information, manage sites, track events, generate reports, and monitor real-time visitor data using the @mackenly/fathom-api SDK
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Website owners monitoring traffic
- / Marketing teams analyzing visitor behavior
- / Developers building analytics dashboards
capabilities
- / Retrieve account information
- / List and manage tracked websites
- / Generate analytics reports with custom filtering
- / Track real-time visitor data
- / List events for specific sites
- / Create aggregated data views
what it does
Connects to Fathom Analytics to retrieve website traffic data, visitor stats, and analytics reports through AI assistants.
about
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.
how to install
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.
license
MIT
Fathom Analytics is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
MCP Fathom Analytics
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>Features
The MCP server provides the following Fathom Analytics tools:
Account Information
get-account: Retrieve details about your Fathom Analytics account
Sites Management
list-sites: List all your Fathom Analytics sites
Events
list-events: List events for a specific site
Analytics
get-aggregation: Generate aggregated analytics reports with flexible filtering and grouping options
Visitor Tracking
get-current-visitors: Get real-time data about current site visitors
Usage
If 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
API Structure
The MCP server uses the @mackenly/fathom-api SDK to interface with the Fathom Analytics API endpoints:
- Account API:
https://api.usefathom.com/v1/account - Sites API:
https://api.usefathom.com/v1/sites - Events API:
https://api.usefathom.com/v1/sites/SITE_ID/events - Aggregation API:
https://api.usefathom.com/v1/aggregations - Current Visitors API:
https://api.usefathom.com/v1/current_visitors
Aggregation Examples
The aggregation tool is highly flexible. Here are some example use cases:
- Daily pageview statistics for the last 30 days:
{
"entity": "pageview",
"entity_id": "SITE_ID",
"aggregates": "pageviews,uniques,visits",
"date_grouping": "day",
"date_from": "2023-08-01 00:00:00"
}
- Performance of individual pages:
{
"entity": "pageview",
"entity_id": "SITE_ID",
"aggregates": "pageviews,uniques,avg_duration",
"field_grouping": "pathname",
"sort_by": "pageviews:desc",
"limit": 10
}
- Traffic from specific countries:
{
"entity": "pageview",
"entity_id": "SITE_ID",
"aggregates": "visits",
"field_grouping": "country_code",
"sort_by": "visits:desc"
}
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
This project is licensed under the MIT License - see the LICENSE file for details.
FAQ
- What is the Fathom Analytics MCP server?
- Fathom Analytics is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Fathom Analytics?
- This profile displays 56 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.8 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
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
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
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
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ 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.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.8★★★★★56 reviews- ★★★★★Daniel Robinson· Dec 24, 2024
I recommend Fathom Analytics for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Layla Menon· Dec 24, 2024
Fathom Analytics is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Benjamin Torres· Dec 16, 2024
We evaluated Fathom Analytics against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Kaira Yang· Dec 12, 2024
Fathom Analytics is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Daniel Thompson· Dec 8, 2024
Fathom Analytics is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Amelia Thompson· Nov 27, 2024
Fathom Analytics is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Kabir Johnson· Nov 23, 2024
I recommend Fathom Analytics for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Yash Thakker· Nov 19, 2024
We evaluated Fathom Analytics against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Chen Johnson· Nov 3, 2024
Fathom Analytics is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Kiara Robinson· Oct 22, 2024
According to our notes, Fathom Analytics benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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