MCP Server

Modern teams increasingly work through AI assistants — drafting in Claude, building in Cursor, automating with agents. Every SaaS dashboard that can't join those conversations forces a context switch: open the tab, find the number, copy it over. The Model Context Protocol solves this by letting an AI agent query data sources directly. For GEO data, that's especially natural: the questions you ask of it — what changed, who's winning, where are gaps — are exactly the kind an assistant answers well.

On Expansion and Scale plans, you connect Geonimo's MCP server to your client of choice. From then on, your assistant can pull live GEO data mid-conversation: "How did our visibility trend this month versus last?", "Which domains gained citations in our category?", "List prompts where our top competitor beats us." The data arrives inside whatever you're already doing — a strategy doc, a code session, a planning thread — with no exports and no copy-paste.

The MCP server turns Geonimo into infrastructure. Consultants generate client-ready summaries by asking Claude to combine Geonimo data with their own templates. Technical teams wire GEO metrics into internal tools and automations through Cursor. Power users build weekly routines where an assistant reviews visibility, flags anomalies and drafts the internal update. Anything Geonimo measures becomes raw material for your own GEO workflows — which is exactly how a platform should behave.