"How to Embed MCP into a Django Application" matching MCP servers:

Integrates 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.

Bridges Django applications with AI assistants by implementing the Model Context Protocol, enabling AI to interact with Django data and functionality through simple decorators.

A 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.

A Django MCP server that exposes tools and resources to AI agents using simple decorators, with auto-discovery, type safety, and custom authentication.

A Django-native MCP application and tool registration framework inspired by Celery, providing async tool definitions, autodiscovery, and stdio/Streamable HTTP serving built on the official MCP Python SDK.

Provides a stateful Django shell environment that allows AI assistants to execute Python code directly against Django projects. Maintains persistent session state between calls, enabling iterative exploration of models, queries, and debugging.

Automatically exposes Django REST Framework endpoints as MCP tools with zero configuration, supporting multiple transports and authentication.

Stateless MCP server for Django, enabling Django applications to interact via the Model Context Protocol.

Expose Django admin models to MCP clients for CRUD, admin actions, model introspection, and more via HTTP with token authentication.

Exposes Django runtime information (settings, apps, URLs, models, migrations) as MCP resources for AI agents to inspect a live Django project without static analysis.

Enables developers to analyze Django projects for risky code patterns such as cascade delete impact, N+1 queries, unsafe migrations, and unscoped tenant reads through MCP tools and a CLI.

Static-analysis MCP server for Django models. 5 read-only tools for AI coding agents.

Exposes the Django admin as an MCP server, letting authorized staff interact with admin models via natural language while delegating all permissions to the existing ModelAdmin.

Exposes Django admin's ModelAdmin as MCP tools, with identical permissions, form validation, and session authentication.

Exposes Django REST Framework APIs as MCP tools, enabling natural language interactions with your data models such as CRUD operations and custom actions, with automatic schema generation from DRF serializers.

An implementation of the Model Context Protocol for Django that enables AI agents to interact with applications by exposing models, logic, and REST Framework APIs as tools.

Introspects a Django REST API's OpenAPI schema and exposes each endpoint as an MCP tool, enabling Claude or any MCP client to interact with the API via natural language.

Provides AI assistants easy access to Django best practices by splitting comprehensive styleguide documentation into AI-friendly sections accessible through the Model Context Protocol.

Enables natural language interaction with Django REST Framework APIs by auto-discovering ViewSets and providing CRUD tools, requiring minimal setup.

A Model Context Protocol service that wraps Django's migration commands as MCP endpoints, making it easy to manage migrations across multiple services and integrate with CI/CD pipelines.