MCP Django Shell
An MCP server that provides stateful Django shell interaction for AI assistants, allowing direct execution of Python code in a Django project and maintaining session state
rating : 2.5 points
downloads : 0
What is mcp-django-shell?
mcp-django-shell is an MCP server specifically designed for AI assistants. It provides a persistent Django shell environment. AI assistants can execute Python code in this environment and interact with your Django project. All imports and variable states will be maintained across multiple calls.How to use mcp-django-shell?
After installation, simply run the server in your Django project directory and then configure the connection in your AI client. AI assistants can then explore your data models, test queries, debug issues, etc. through simple Python code.Use cases
It is very suitable for debugging Django projects, data exploration, API testing, and code prototyping during the development phase. AI assistants can interact with your project just like developers.Main features
Persistent Shell Session
The Python code executed by AI runs in a persistent Django shell environment. The imported modules and defined variables maintain their states across multiple calls.
Full Django Integration
Automatically detect and configure the Django environment, providing full access to the ORM, management commands, and all project features.
Multiple Transport Protocol Support
Supports multiple communication protocols such as STDIO, HTTP, and SSE, and is compatible with different MCP clients.
Session Management
Provides a session reset function to clean up the environment and start over when AI operations encounter problems.
Zero-Configuration Startup
Automatically detect Django settings and start and use quickly without complex configuration.
Advantages
๐ค AI-Friendly Design: Optimized specifically for AI assistants, providing a natural code execution interface
๐ State Persistence: Avoid the need to re-import and set up the environment for each call
๐ Quick Integration: Installation and configuration can be completed within minutes
๐ง Development Efficiency: Significantly improve the efficiency and accuracy of AI-assisted development
๐ Wide Compatibility: Supports multiple MCP clients and transport protocols
Limitations
โ ๏ธ Security Risks: Using in a production environment may lead to data loss or security vulnerabilities
๐ Permission Control: Lack of fine-grained permission control mechanisms
๐ Performance Overhead: Maintaining a shell session continuously requires additional resources
๐ก๏ธ Limited Protection: Relies on the security protection mechanisms of the AI model itself
How to Use
Install the Package
Install the mcp-django-shell package using pip or uv
Start the Server
Start the MCP server in your Django project directory
Configure the Client
Add the MCP server configuration to your AI client
Start Using
The AI assistant can now interact with your project through the django_shell tool
Usage Examples
Data Model Exploration
AI assistants explore the database model structure and data
API Testing
Test Django REST framework or other API endpoints
Problem Debugging
Help diagnose and fix problems in the code
Data Migration Verification
Verify the correctness of data migration scripts
Frequently Asked Questions
Is this tool safe? Can it be used in a production environment?
Which Django versions are supported?
How to reset the AI session state?
Which MCP clients are supported?
What should I do if there are import errors or configuration problems?
Related Resources
PyPI Project Page
Official PyPI package page, containing the latest version and download information
GitHub Repository
Source code and contribution guidelines
Model Context Protocol Specification
Official MCP specification and documentation
Django Documentation
Official Django documentation
Contribution Guidelines
How to contribute code to the project

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