Search the docs over MCP

This documentation site is itself a hosted MCP server. Point an agent at it and it gets two tools: search_docs, which returns the handful of relevant doc sections for a query — excerpts plus deep links, not whole pages — and get_doc, which reads one full page as clean Markdown. The agent connects once and pulls in exactly the passage it needs, instead of loading the whole manual on every turn.

Connect

The server lives at https://stitchapi.dev/api/mcp. It needs no key. Drop one of these into your agent's config.

Claude Code — add it from the CLI:

claude mcp add --transport http stitchapi-docs https://stitchapi.dev/api/mcp

or commit it to the project's .mcp.json:

{
    "mcpServers": {
        "stitchapi-docs": {
            "type": "http",
            "url": "https://stitchapi.dev/api/mcp"
        }
    }
}

Cursor — .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):

{
    "mcpServers": {
        "stitchapi-docs": {
            "url": "https://stitchapi.dev/api/mcp"
        }
    }
}

VS Code (Copilot) — .vscode/mcp.json; note the top-level key is servers:

{
    "servers": {
        "stitchapi-docs": {
            "type": "http",
            "url": "https://stitchapi.dev/api/mcp"
        }
    }
}

The two tools

search_docs takes a natural-language query and an optional limit (default 5). It runs hybrid retrieval — keyword and semantic together — over the same Markdown that feeds llms.txt, and returns each hit as { title, url, excerpt, score }. The url carries the section anchor, so it deep-links straight to the passage. It never returns full pages: that frugality is the whole point.

get_doc is the escape hatch for when an excerpt isn't enough. Give it the url from a search_docs hit (or a slug like guides/resilience/throttle) and it returns that page as clean Markdown — the same output as its llms.mdx route.

When to reach for it

For a corpus this size, loading the whole llms-full.txt once is still the simplest correct default — it fits a modern context window, so there's nothing to gain from retrieval. Reach for search_docs when one of two things becomes true: the docs outgrow the model's window, or reloading them every turn costs more than a targeted lookup is worth. The index is rebuilt from the docs on every deploy — the same source a human reads — so a search hit never drifts from the page it cites.

See also