AI agents & MCP

RankNibbler is built to be called by AI agents — ChatGPT, Claude, Perplexity and any MCP-compatible client. 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.

GET /api/openapi.json

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.