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Building a Plug-and-Play Marketing Analytics Agent with the Model Context Protocol (MCP)
Over the past few months I’ve been experimenting with the Model Context Protocol.
Think of MCP as the USB-C of the AI world, which is one slim specification that lets language models talk to many data sources and tools without a bespoke adapter for each one.
The open-source community is moving quickly here, and the spec already powers integrations in products like Claude Desktop, Cursor, Windsurf, and many projects I’ve seen on GitHub.
Today I’d like to walk you, step by step, through a small but realistic marketing-analytics scenario that shows the value of MCP in enterprise settings. By the end you’ll have:
- Mock marketing data living in a local SQLite database.
- An MCP SQLite server exposing that database.
- A host application (say Claude Desktop) querying it conversationally.
- A clear sense of pitfalls and production-grade extensions.
Why bother?
Marketing teams live on weekly CSV exports.
Facebook Ads performance, TikTok spend, LinkedIn leads, you name it.
Every platform’s format differs, and each team slices the data differently.
