Claude-First Analytics MCP Server: Giving AI Agents Direct Access to Web Analytics Context

One developer took their existing analytics tool (which sent an AI summary to users every Sunday) and rebuilt it as a Claude-first MCP server. The core hypothesis: if your agent has access to web analytics, your code, your database, and other sources, it has better context to advise and improve your product.

What's in the MCP Server?

The new server — hosted at lodd.dev — exposes a set of tools that give Claude access to:

• Simple web analytics — standard pageviews, visitors, etc.
• Trackable links — analytics with UTM or similar tracking parameters.
• Product insight — usage data and trends.

These are exposed as MCP tools, meaning Claude can directly query them during a conversation or task. The author is experimenting with claude.md instructions to prompt Claude to actually use the context, but notes that hooks may be needed to ensure the agent acts on the data.

Why This Matters

Most AI coding agents today work with code context but lack real product/usage data. By bringing analytics into the MCP tool ecosystem, Claude can ground its suggestions in actual user behavior. For instance, an agent could recommend which feature to optimize based on real usage patterns, or suggest A/B test results to consider during a refactor.

Try It Yourself

You can point Claude to lodd.dev/llms.txt to pull the tool definitions, or explore the server at lodd.dev.

Who It's For

Developers building AI agent workflows who want their Claude agents to make data-informed decisions by having direct access to web analytics alongside code and database context.