Lamatic Docs MCP

Query Lamatic.ai documentation instantly from any AI assistant. No searching, no tab switching, just answers.

What is the Docs MCP?

The Lamatic Docs MCP is a Model Context Protocol server that gives AI assistants like Claude, Cursor, and Windsurf direct access to Lamatic.ai documentation, and to the Lamatic AgentKit repository of kits, bundles, and templates.

It is powered by a RAG pipeline built entirely on Lamatic:

Firecrawl scrapes the docs
Chunking + Vectorize indexes them into a VectorDB
RAG Node answers questions semantically
Next.js + Vercel exposes the MCP endpoint publicly

The MCP is free to use. No API key or account required.

Install

Pick your client and you’re connected in a few seconds.

Add to Cursor Add to VS Code

Claude Code

claude mcp add --transport http lamatic-docs https://docmcp.lamatic.ai/api/mcp

Claude Desktop, Windsurf, Cline, and other clients

Add this to your MCP client config:

{
  "mcpServers": {
    "lamatic-docs": {
      "url": "https://docmcp.lamatic.ai/api/mcp"
    }
  }
}

For Claude Desktop specifically, the config file lives at:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json

Restart the client after saving. You should see a 🔌 tools icon in the chat input.

Available Tools

`query_docs`

Ask any question about Lamatic.ai documentation. Uses RAG to search across all indexed docs and return a precise answer with references.

Input:

Parameter	Type	Required	Description
`text`	string	✅	The question to ask

Example:

{
  "name": "query_docs",
  "arguments": {
    "text": "How do I set up a RAG node in Lamatic?"
  }
}

AgentKit tools

These call the Lamatic AgentKit repository directly through the GitHub API, so answers reflect whatever is on the repo right now rather than the indexed vector store. No authentication is required for any of these.

Tool	What it does
`kit_list`	Lists every kit, bundle, and template available in AgentKit
`kit_get`	Returns the full details for one kit: its `lamatic.config.ts`, README, and list of flows
`kit_search`	Searches kits by type (kit, bundle, or template) and/or a free-text keyword
`kit_get_flow`	Returns the raw `.ts` source for a specific flow inside a kit
`kit_check_pr_status`	Checks the structural and Studio runtime validation status of an open AgentKit pull request

⚠️

A few more tools exist for people actively contributing kits — kit_validate_structure, kit_auth_login, and kit_revalidate_pr. These either touch your local filesystem or post GitHub comments, so they only run when you’re running the server locally over stdio, never on the public hosted endpoint.

How It Works

Your Question
      ↓
MCP Client (Claude / Cursor)
      ↓
docmcp.lamatic.ai/mcp/api
      ↓
Lamatic RAG Flow
      ↓
VectorDB (indexed Lamatic docs)
      ↓
Answer

The entire pipeline is built on Lamatic:

Indexing Flow: scrapes lamatic.ai/docs using Firecrawl, chunks content, vectorizes and stores in VectorDB
Query Flow: takes your question, runs semantic search, generates answer
MCP Server: Next.js API route deployed on Vercel, calls the query flow via GraphQL

Supported Clients

Client	Supported
Claude Desktop	✅
Claude Code	✅
Cursor	✅
VS Code (Copilot)	✅
Windsurf	✅
Cline	✅
Any HTTP MCP client	✅

Source Code

The MCP is open source. You can view, fork, and contribute on GitHub:

github.com/Lamatic/Lamatic-MCP-Docs

Want to build your own Docs MCP for your company? See the Build Your Own Docs MCP guide. Fork the repo, connect your own Lamatic flow, and deploy to Vercel in minutes.

Other Lamatic MCP Servers

Graph MCP: Execute your deployed Lamatic flows via AI agents

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