Is there an MCP server for AI visibility or GEO? Yes. GEOly runs one at app.geoly.ai/api/mcp. It exposes GEO data — prompt-by-prompt visibility across ChatGPT, Gemini, Google AI Mode, Perplexity and Copilot, rank, sentiment, citations, product-card presence in AI shopping — as tools that any MCP-compatible client can call. Claude Code, Cursor, Codex, a custom agent: if it speaks MCP, it can query visibility data mid-task.
And if your question is the terminal version, an AI visibility CLI you can run from a shell or a cron job, that exists too: a single zero-dependency binary, installed with one curl or PowerShell line, that prints pure JSON to stdout and returns exit codes your scripts can branch on — built for Claude Code, Codex, n8n and CI pipelines, documented at geoly.ai/open/cli. GEOly ships three surfaces on one tool source: the MCP server for agents inside dev tools, the CLI for scripts and CI, and GEO skills that package full audits into a single invocation. Same tools, same definitions, so numbers never drift between surfaces. So yes, you can automate GEO audits end to end.
The reason this setup exists is simple. GEO work increasingly happens inside dev tools, because the fix for a losing prompt is almost never in a dashboard. It lives in a schema block in a product template, a stale price in a feed, a missing comparison page in the content repo. Visibility data locked behind a web UI can't join that workflow. MCP turns it into a callable tool, so the audit happens where the fix happens: your codebase.
What the GEOly MCP server exposes
The server exposes up to 62 tools across two data planes, returned as structured responses an agent can reason over. The brand plane covers your own tracking: KPIs, prompt-level visibility, citations, competitors, GEO audits, GA4 — plus write operations, so an agent can create prompts, topics and competitors, or trigger a monitoring run. The industry plane needs no configuration at all: category rankings, white space, brand momentum, Share of Card, AI search demand and citation sources, queryable for any brand in the public dataset:
- Prompt-level visibility: for each tracked prompt, which AI engines mention the brand, at what rank, with what sentiment, and which sources the answer cites
- Share of Card: whether your products appear as product cards in ChatGPT shopping and Google AI Mode, and whose cards show up when yours don't
- Citation sources: the domains and pages AI engines actually cite for your category's prompts — the target list for content and earned-media work
- Competitor share of voice: mention share across a prompt set, tracked over time
- ChatGPT ads intelligence: which advertisers appear on which prompts, useful for spotting paid pressure on queries you hold organically
