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.
Exposes Django runtime information (settings, apps, URLs, models, migrations) as MCP resources for AI agents to inspect a live Django project without static analysis.
An MCP server for inspecting and interacting with Pydantic models and Python type contracts. It enables LLMs to perform deterministic validation, schema generation, model explanation, and Pydantic v1 to v2 migration analysis.
A local, read-only MCP server that analyzes Python backend projects by providing tools to scan, map, and selectively read files, reducing token usage for AI clients.
This MCP server enables AI models to analyze local Python codebases using abstract syntax trees, providing tools for file structure analysis, symbol search, import graphing, docstring auditing, and refactoring prompts without loading entire source files into context.
