Skip to main content
Glama

DRF MCP

PyPI version Python 3.10+ Django 4.2+ License: MIT

Enterprise-grade Model Context Protocol (MCP) integration for Django REST Framework with FastMCP 3.0

Automatically expose your Django REST Framework APIs as tools for AI agents via the Model Context Protocol. Zero configuration, maximum security, enterprise-ready.

Overview

DRF MCP transforms your Django REST Framework views into AI-native tools via the Model Context Protocol standard. Built on FastMCP 3.0, it automatically:

  • 🔍 Discovers all DRF views and ViewSets in your Django URLconf

  • 🔧 Exposes them as MCP tools with auto-generated JSON schemas

  • 🔐 Secures with DRF's permission system (no security bypass)

  • Async-first execution for non-blocking LLM interactions

  • 📊 Traces with OpenTelemetry for observability

  • 🚀 Scales with stateless, transport-agnostic architecture

Related MCP server: mcp-django-server

Quick Start

# In your Django project
from drf_mcp import DRFMCP
from myapp.views import CustomerViewSet

# Initialize MCP server
mcp = DRFMCP("MyEnterpriseAPI")

# Option 1: Register specific ViewSets
mcp.register_viewset(CustomerViewSet, namespace="crm")

# Option 2: Auto-discover all DRF views
mcp.autodiscover()

# Run server (stdio, HTTP, or SSE transport)
if __name__ == "__main__":
    mcp.run()

Your DRF serializers automatically become MCP tool parameters. No extra configuration needed.

Architecture

Discovery

Scans Django's URLconf to find all DRF APIView and ViewSet classes.

Schema Generation

Uses drf-spectacular to convert DRF serializers into JSON schemas for MCP tool arguments.

Execution

Wraps DRF view invocations with async support, permission checking, and error handling.

Security

Enforces DRF's authentication and permission classes on every tool call. Agents are authenticated users.

Transport

Supports stdio, HTTP, and SSE via FastMCP's built-in transports.

Features

  • ✅ Automatic DRF view discovery and MCP tool generation

  • ✅ drf-spectacular schema integration (nested serializers, complex validators)

  • ✅ DRF permission system integration (no security bypass)

  • ✅ Async-first executor (non-blocking LLM execution)

  • ✅ OAuth2/OIDC agent authentication

  • ✅ OpenTelemetry tracing for observability

  • ✅ Interactive manage.py mcp_inspector CLI

  • ✅ Type hints and Pydantic v2 schemas

  • ✅ Django 4.2 LTS and 5.0+ support

  • ✅ Python 3.10+ support

Installation

uv add drf-mcp

Or with pip:

pip install drf-mcp

Documentation

Full documentation is available at drf-mcp.readthedocs.io

Requirements

  • Python: 3.10+

  • Django: 4.2+ (LTS) or 5.0+

  • Django REST Framework: 3.14+

  • FastMCP: 3.0+

Development

# Clone and setup
git clone https://github.com/ziyacivan/drf-mcp.git
cd drf-mcp
uv venv
uv pip install -e ".[dev]"

# Run tests
pytest

# Format code
black src/drf_mcp tests
isort src/drf_mcp tests

# Type checking
mypy src/drf_mcp

License

MIT License - See LICENSE file for details.

Contributing

Contributions welcome! Please see CONTRIBUTING.md for guidelines.

Acknowledgments

A
license - permissive license
-
quality - not tested
C
maintenance

Maintenance

Maintainers
Response time
Release cycle
1Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ziyacivan/drf-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server