AI agents & MCP
RankNibbler is built to be called by AI agents — ChatGPT, Claude, Perplexity and any MCP-compatible client. 40 authenticated endpoints, all available on every plan. Two ways to wire it in.
OpenAPI spec (custom GPT actions)
Point a custom GPT Action at the machine-readable spec and configure one API key. Users can then just say "audit this site" and the agent calls RankNibbler directly.
MCP server
Run our Model Context Protocol server to expose tools like audit_url to any MCP client — Claude Desktop, IDEs and agent frameworks. The server lives in mcp/ in the repo and proxies to the live API with your key.
Why it works well for agents
- One call, structured JSON — no scraping, parsing or browser automation for the agent to do.
- Live endpoints — instant responses, no async task polling to orchestrate.
- Clear errors — consistent status codes and messages the agent can reason about.
- No third-party spend — no endpoint calls a paid per-request data vendor, so an agent can't run up a bill by looping.
Endpoints agents get the most out of
- /api/v1/page-metrics Beta — one call for SEO, accessibility, security and AI-search signals, so an agent doesn't have to fan out across five endpoints.
- /api/v1/citability Beta — score how quotable a page is for answer engines, or score an agent's own draft before it publishes. The API runs the deterministic scorer only: it never calls a model provider.
- /api/v1/page-diff Beta — hand an agent a structured before/after so it can report exactly what a change did.
- /api/v1/usage Beta — let a long-running agent check its own remaining quota and back off.
Endpoints marked Beta are new: live and callable, but their response shape may still change — pin what you parse.
What the API does not return
Worth telling an agent up front, so it doesn't ask: this is an on-page and technical SEO API. There is no backlink data, no keyword search volume, no SERP positions and no competitor rankings. Only Lighthouse, screenshot and waterfall involve a real browser; every other endpoint analyses the served HTML.