Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"django-ai-boost": {
"env": {
"PYTHONPATH": "/path/to/your/django/project",
"DJANGO_MCP_AUTH_TOKEN": "your-secret-token",
"DJANGO_SETTINGS_MODULE": "myproject.settings"
},
"args": [
"--settings",
"myproject.settings",
"--transport",
"sse"
],
"command": "django-ai-boost"
}
}
}Are you the author?
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A Model Context Protocol (MCP) server for developing Django applications, inspired by Laravel Boost. This server exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.
Run this in your terminal to verify the server starts. Then let us know if it worked — your result helps other developers.
uvx 'django-ai-boost' 2>&1 | head -1 && echo "✓ Server started successfully"
After testing, let us know if it worked:
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A Model Context Protocol (MCP) server for developing Django applications, inspired by Laravel Boost. This server exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.

Django AI Boost MCP server providing Django project introspection through AI assistants (Example using OpenCode)
# Using uv (recommended)
uv pip install django-ai-boost
# Or with pip
pip install django-ai-boost
If you want to contribute or run the latest development version:
# Clone the repository
git clone https://github.com/vinta/django-ai-boost.git
cd django-ai-boost
# Install uv if you haven't already
# On macOS/Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
# On Windows:
powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
# Install dependencies (creates virtual environment automatically)
uv sync --dev
# Verify installation
uv run django-ai-boost --help
The server requires access to your Django project's settings:
# Set the Django settings module
export DJANGO_SETTINGS_MODULE=myproject.settings
django-ai-boost
# Or specify settings directly
django-ai-boost --settings myproject.settings
# Run with SSE transport (default is stdio, which doesn't use network ports)
django-ai-boost --settings myproject.settings --transport sse
# Run with SSE transport on a custom port (default port is 8000)
django-ai-boost --settings myproject.settings --transport sse --port 3000
# Run with SSE transport on custom host and port
django-ai-boost --settings myproject.settings --transport sse --host 0.0.0.0 --port 8080
Note: The stdio transport (default) communicates via standard input/output and does not use network ports. The --port and --host options only apply when using --transport sse.
Django AI Boost supports bearer token authentication for secure production deployments when using SSE transport.
Set authentication token (recommended for production):
export DJANGO_MCP_AUTH_TOKEN="your-secret-token"
django-ai-boost
... [View full README on GitHub](https://github.com/vintasoftware/django-ai-boost#readme)