Django Styleguide

You can access and read Django Styleguide content through an MCP server that you run with an MCP client. This server provides a centralized, AI-friendly source of Django best practices for models, services, APIs, serializers, and related topics, making it easy to fetch relevant sections and keep your knowledge up to date.

How to use

You connect to the MCP server from your MCP client to search, fetch, and read documentation sections relevant to Django best practices. Start by listing available sources, fetch the llms.txt index, and then request the specific sections you need. The server organizes content into structured sections so you can quickly locate topics like models, services, APIs, serializers, URLs, and settings.

How to install

Prerequisites you need on your machine include Node.js or Python, depending on the runtime you plan to use, plus an MCP client compatible with the MCP protocol.

Step by step flow to run the Django Styleguide MCP server locally:

{
  "mcpServers": {
    "django_styleguide": {
      "command": "uvx",
      "args": [
        "--from",
        "mcpdoc",
        "mcpdoc",
        "--urls",
        "DjangoStyleguide:https://raw.githubusercontent.com/dmmeteo/django-styleguide-mcp/main/llms.txt",
        "--transport",
        "stdio"
      ]
    }
  }
}

Configuration and usage notes

The server is designed to be consumed by MCP clients that can query available sources, read llms.txt, and fetch specific documentation sections. Use the provided MCP configuration to start the server with the correct URLs and transport method.

Security and maintenance notes

Keep the llms.txt index up to date by periodically updating the source documentation and regenerating the index. Use secure transports and restrict access to trusted MCP clients to prevent unwanted changes or data exposure.

Troubleshooting

If you cannot fetch sections, verify that the llms.txt URL is reachable and that the MCP client is configured to use the stdio transport with the correct command and arguments. Check for updates to the mcpdoc_split tooling if you regenerate documentation.

Available tools

mcpdoc_split

CLI to split large documentation sources into modular, AI-friendly files and generate llms.txt indexes.

uvx

MCP runtime used to run and serve MCP configurations from a standard input/output interface.