MCP server
StitchAPI Docs Official
dev.stitchapi/docs
Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools
Search and read the StitchAPI docs: search_docs finds relevant sections, get_doc reads a page.
Working at last checkVerified publisher: stitchapi.devAbout 312 tokens per request once connected2 tools
https://stitchapi.dev/api/mcp
At a glance
- Type
- MCP server
- Publisher
- stitchapi.dev (verified by the MCP Registry)
- Status
- Working at last check
- Tools
- 2
- Token cost
- About 312 tokens per request
- Sets up in
- Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok
- Last checked
- 26 Oct 2026, 08:29 UTC
Connect it to your agent
Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.
Claude Code
claude mcp add --transport http docs https://stitchapi.dev/api/mcp
Claude Desktop
Settings → Connectors → Add custom connector, and paste the URL.
Codex (config.toml)
[mcp_servers.docs] url = "https://stitchapi.dev/api/mcp"
Gemini CLI
{"mcpServers":{"docs":{"httpUrl":"https://stitchapi.dev/api/mcp"}}}
Cursor
{"mcpServers":{"docs":{"url":"https://stitchapi.dev/api/mcp"}}}
VS Code
{"servers":{"docs":{"type":"http","url":"https://stitchapi.dev/api/mcp"}}}
Antigravity
agy mcp add docs https://stitchapi.dev/api/mcp
ChatGPT
Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.
OpenAI API (Responses tools)
{"type":"mcp","server_label":"docs","server_url":"https://stitchapi.dev/api/mcp","require_approval":"always"}
Grok (xAI API tools)
{"type":"mcp","server_label":"docs","server_url":"https://stitchapi.dev/api/mcp"}
Tools
get_doc~152 tokens
Fetch a full StitchAPI documentation page as Markdown — the "read the whole thing" escape hatch for a search_docs hit. Pass a `url` (as returned by search_docs) or a `slug` like "guides/resilience/throttle".search_docs~160 tokens
Search the StitchAPI documentation semantically (hybrid BM25 + vector). Returns the most relevant doc sections as excerpts with deep links — never full pages. Follow up with get_doc to read a full page.
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