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

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.

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.

Enables tracking job applications by connecting Gmail to retrieve emails, process job details, manage statuses, and generate statistics.

Local MCP server for A-share stock trading via Tonghuashun, offering account/position queries, buy/sell/cancel orders with risk controls and forced user confirmation; currently simulated with a reserved interface for real broker channels.

Enables agents to convert Markdown into WhatsApp-compatible formatting, including styled text, lists, and tables that fit a phone's monospace width.

Minimal MCP server for sending messages to Poke via the inbound webhook.

Converts REST API code (like NestJS controllers or FastAPI endpoints) to Postman collections and environments, helping developers automatically sync their API endpoints with Postman.

Turn natural language into 3D models in Fusion 360. 64 CAD tools including sketches, extrudes, fillets,and JIS standard parts.

Automates the conversion of Figma designs into TypeScript React components and integrates with GitHub to create pull requests for the generated code. It includes visual regression testing with Playwright and accessibility validation to ensure implementations match the original designs.

Allows Cursor AI to communicate with Figma for reading designs and modifying them programmatically through a Model Context Protocol integration.

Enables AI agents like Claude to interact with Figma designs through 50+ tools for creating, styling, and manipulating design elements, components, and variables via a WebSocket relay and Figma plugin.

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

Enables forwarding Douyin or Bilibili video shares to Kimi for AI analysis and automatically writing the resulting Chinese notes into an Obsidian vault.

A development server that automatically discovers and exposes tools from the src/tools directory, allowing you to create and run Machine Comprehension Protocol (MCP) services with either HTTP or STDIO transport methods.

A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.

Converts Figma designs into React components with TypeScript and Tailwind CSS by extracting components from Figma files and transforming them into ready-to-use code.

Automatically converts Swagger/OpenAPI specifications into dynamic MCP tools, enabling interaction with any REST API through natural language by loading specs from local files or URLs.

An MCP server that enables AI assistants to interact with Figma designs for tasks like reading document info, creating elements, and managing auto layouts. It facilitates real-time design automation via a custom Figma plugin and WebSocket server integration.

Enables users to control the cursor in Figma through verbal commands using an agentic AI agent, streamlining the design process with a new interaction method.

Enables Cursor AI to interact with Figma designs, allowing users to read design information and programmatically modify elements through natural language commands.