A customized version of the MCP documentation server that enables integration between LLM applications (like Cursor, Claude Desktop, Windsurf) and
If you want an AI assistant working directly with MCP Doc, the mcp doc mcp server is the bridge. A customized version of the MCP documentation server that enables integration between LLM applications (like Cursor, Claude Desktop, Windsurf) and documentation sources via the Model Context Protocol.
A customized version of the MCP documentation server that enables integration between LLM applications (like Cursor, Claude Desktop, Windsurf) and documentation sources via the Model Context Protocol.
This server provides MCP host applications with: 1. Access to specific documentation files (langgraph.txt and mcp.txt) 2. Tools to fetch documentation from URLs within those files
Once connected, the assistant can call this tool directly:
Cursor — Then add these instructions to Cursor's Custom Instructions:Setup follows the standard MCP pattern: clone or install the server, then register it in your client's configuration file and restart the client. The configuration snippets on this page cover Claude Desktop, Claude Code and Cursor.
Knowledge and memory servers address the most frustrating trait of language models — walking into every conversation with no recollection of the last one. MCP Doc sits in that group, and the shape of its toolset — Cursor — tells you what it is really for. Worth comparing against the other knowledge memory servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.
| Tool | What it does |
|---|---|
| Cursor | Then add these instructions to Cursor's Custom Instructions: |
{
"mcpServers": {
"mcp-doc": {
"command": "uvx",
"args": [
"--from",
"mcpdoc",
"mcpdoc",
"--urls",
"LangGraph:https://raw.githubusercontent.com/esakrissa/mcp-doc/main/docs/langgraph.txt",
"ModelContextProtocol:https://raw.githubusercontent.com/esakrissa/mcp-doc/main/docs/mcp.txt",
"--allowed-domains",
"*",
"--transport",
"stdio"
]
}
}
}Configuration as documented by the project. Restart the client after saving.
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.