django-native-mcp
Provides a Django-native framework for exposing tools defined in Django apps as MCP endpoints, including autodiscovery, management commands, and Streamable HTTP/stdio serving.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@django-native-mcplist the available MCP tools in this Django project"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
django-native-mcp
A small Django-native MCP application and tool registration framework inspired by Celery.
It delegates protocol handling, schemas, validation, serialization, stdio, and Streamable HTTP
to the official mcp Python SDK.
This is not another wrapper around FastMCP, the dependencies are only native Python SDK
Installation
pip install django-native-mcpAdd the application and its configuration:
# settings.py
INSTALLED_APPS = [
# ...
"django_native_mcp",
]
DJANGO_NATIVE_MCP = {
"APP": "config.mcp:app",
}Create the application:
# config/mcp.py
from django_native_mcp import MCP
app = MCP("backend")
app.autodiscover_tools()Declare tools explicitly in installed Django apps:
# orders/mcp.py
from django_native_mcp import shared_tool
from .models import Order
@shared_tool
async def get_order(order_id: int) -> dict:
"""Get an order."""
order = await Order.objects.aget(pk=order_id)
return {"id": order.pk, "status": order.status}The registered name is orders.get_order, using the Django application label.
python manage.py mcp_list
python manage.py mcp_inspect orders.get_order
python manage.py mcp_call orders.get_order '{"order_id": 1}'
python manage.py mcp_serve --transport stdioTools must use async def. The framework does not add implicit threads or sync_to_async.
Related MCP server: django-mcp
Direct application tools
from django_native_mcp import MCP
app = MCP("backend")
@app.tool(name="system.health")
async def health() -> dict:
return {"ok": True}@app.tool binds immediately to one application. @shared_tool remains application-independent
until autodiscovery binds it.
Streamable HTTP with Django
The official SDK ASGI app can be served alone:
application = app.asgi_app()Or route /mcp to MCP and everything else to Django:
# config/asgi.py
import os
from django.core.asgi import get_asgi_application
from django_native_mcp.asgi import MCPApplication
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "config.settings")
django_application = get_asgi_application()
# Import the MCP app only after Django's application registry is ready.
from config.mcp import app as mcp_app
application = MCPApplication(
django=django_application,
mcp=mcp_app,
mcp_path="/mcp",
)The dispatcher forwards ASGI lifespan to the official MCP application, so its transport lifecycle is started and stopped by the outer ASGI server.
Testing
Use the thin wrapper around the official in-process client:
from django_native_mcp.testing import MCPTestClient
async with MCPTestClient(app) as client:
result = await client.call_tool("orders.get_order", {"order_id": 1})End-to-end example
The example/ directory contains a runnable Django project using the built-in auth
User, a Streamable HTTP MCP endpoint, and a standalone OpenAI Responses API client that discovers
and calls the Django tool through MCP.
Architecture
Django apps / mcp.py
↓
shared_tool → ToolDefinition → ToolRegistry → MCP
↓
official MCPServer
↙ ↘
stdio Streamable HTTPThe registry is process-local and becomes read-only when its official server is created. Each worker builds the same registry from source during startup.
Non-goals
This package is not an MCP protocol implementation, ORM-to-MCP generator, REST/DRF adapter, Celery replacement, background queue, or AI-agent framework. It does not automatically expose Django models and does not infer permissions from them.
License
MIT
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceA Django MCP server that exposes tools and resources to AI agents using simple decorators, with auto-discovery, type safety, and custom authentication.MIT
- AlicenseNot gradedqualityFmaintenanceIntegrates MCP tool hosting into Django applications, enabling easy definition and serving of MCP tools, resources, and prompts via ASGI with support for URL path parameters and logging.72MIT
- AlicenseNot gradedqualityBmaintenanceA Model Context Protocol (MCP) server for developing Django applications. It exposes Django project information through MCP tools, enabling AI assistants to better understand and interact with Django codebases.109MIT
- AlicenseNot gradedqualityCmaintenanceExposes Django REST Framework APIs as MCP tools for AI agents via the Model Context Protocol, with automatic discovery and security.1MIT
Related MCP Connectors
An MCP server that let you interact with Cycloid.io Internal Development Portal and Platform
Your DRF API as MCP tools — 1,800 endpoints become 16 dispatchers, permissioned by Django.
Official Sevalla MCP — full PaaS API access through just 2 tools.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/xelaxela13/django-native-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server