LLMS.txt Documentation

by langchain-ai

307 23k downloads Not rated yet MIT

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Provides AI systems with access to documentation from llms.txt files by fetching and parsing content from specified URLs, enabling seamless documentation lookup during coding sessions.

Details

Repository: langchain-ai/mcpdoc
License: MIT

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Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below
Plugin Name LLMS.txt Documentation

Command (node, npx, python, etc.) uvx
Arguments
- Argument 1 --from
- Argument 2 mcpdoc
- Argument 3 mcpdoc
- Argument 4 --urls
- Argument 5 LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt
- Argument 6 --transport
- Argument 7 stdio
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

JSON

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

From the repository

Please see official uv docs for other ways to install uv.

curl -LsSf https://astral.sh/uv/install.sh | sh

Both YAML and JSON configuration files should contain a list of documentation sources.

Each source must include an llms_txt URL and can optionally include a name:

json [ { "name": "LangGraph Python", "llms_txt": "https://langchain-ai.github.io/langgraph/llms.txt" } ]

python from mcpdoc.main import create_server

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "llms.txt documentation": {
            "env": {},
            "args": [
                "--from",
                "mcpdoc",
                "mcpdoc",
                "--urls",
                "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
                "--transport",
                "stdio"
            ],
            "shell": false,
            "command": "uvx"
        }
    }
}

Linux

{
    "env": [],
    "args": [
        "--from",
        "mcpdoc",
        "mcpdoc",
        "--urls",
        "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
        "--transport",
        "stdio"
    ],
    "shell": false,
    "command": "uvx"
}

Macos

{
    "env": [],
    "args": [
        "--from",
        "mcpdoc",
        "mcpdoc",
        "--urls",
        "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
        "--transport",
        "stdio"
    ],
    "shell": false,
    "command": "uvx"
}

Windows

{
    "env": [],
    "args": [
        "--from",
        "mcpdoc",
        "mcpdoc",
        "--urls",
        "LangGraph:https://langchain-ai.github.io/langgraph/llms.txt LangChain:https://python.langchain.com/llms.txt",
        "--transport",
        "stdio"
    ],
    "shell": false,
    "command": "uvx"
}

You can find llms.txt files for langgraph and langchain here:

| Library | llms.txt |
|------------------|------------------------------------------------------------------------------------------------------------|
| LangGraph Python | https://langchain-ai.github.io/langgraph/llms.txt |
| LangGraph JS | https://langchain-ai.github.io/langgraphjs/llms.txt |
| LangChain Python | https://python.langchain.com/llms.txt |
| LangChain JS | https://js.langchain.com/llms.txt |

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Details

Explore

Setting up with Highlight

From the repository

Claude Desktop / Cursor

Linux

Macos

Windows

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