Cipher is an open-source memory layer framework designed for programming AI agents. It integrates with various IDEs and AI coding assistants through the MCP protocol, providing core functions such as automatic memory generation, team memory sharing, and dual-system memory management.

Refact Agent is an open - source AI programming assistant that supports multi - language code generation, debugging, and optimization. It integrates with mainstream development tools, can be deployed locally, and provides intelligent code completion and code explanation functions.

ai-create-mcp is a Go-based tool for converting OpenAPI specification files into Model Context Protocol (MCP) programs, supporting custom project settings and integration options.

o3 - search - mcp is an MCP server that supports using the OpenAI o3 model and its powerful web search function to help AI programming agents independently solve complex problems.

The Flutter MCP Server is an open - source implementation of the Model Context Protocol (MCP) for the Dart/Flutter ecosystem. It provides a unified API interface for AI assistants and developer tools, supports remote calls to the Dart/Flutter development toolchain, and enables secure and programmable automated development processes.

The OpenFeature MCP Server is a local tool that connects AI programming assistants to OpenFeature capabilities through a standardized protocol, providing SDK installation guidance and feature flag evaluation capabilities, and supporting multiple AI development environments.

SystemPrompt Coding Agent is an open-source project that transforms a local workstation into an AI programming assistant that can be remotely controlled via the MCP protocol, supporting voice commands and mobile operations for off-site programming management.

A Ruby-based AI pair programming MCP server that provides AI-assisted programming functions such as code review, brainstorming, performance analysis, and security check through OpenRouter.

This project provides an OpenAPI specification processing server based on the MCP protocol, which supports dividing large OpenAPI files into multiple small files or extracting specific interfaces to generate new files, facilitating programmatic operations on API documentation by clients such as AI assistants.

The You.com DX Toolkit is an open-source AI development toolkit that includes npm packages, plugins, and skills, and can work in conjunction with more than 20 AI programming assistants such as Claude Code and Cursor. It provides tools such as the MCP server, Vercel AI SDK plugin, and Teams.ai integration, supporting real-time web search, AI agents, and content extraction functions.

Codex Bridge is a lightweight MCP server that connects AI programming assistants with OpenAI Codex through the official CLI, supporting multi - client interaction without API costs.

MCP-openMSX is a bridge project that connects modern AI development with retro computing (MSX systems). It provides a comprehensive control toolset for the openMSX emulator through the MCP protocol, including emulator management, media operations, BASIC programming support, debugging tools, and automation functions.

Photoshop MCP Server is a service that integrates with Adobe Photoshop through the Model Context Protocol (MCP), allowing AI assistants and other MCP clients to programmatically control Photoshop. It provides functions such as creating, opening, and saving documents, operating on layers, and retrieving session information, and only supports the Windows system.

This project is an experimental Aider MCP server used to offload AI programming tasks to the Aider open - source assistant to improve development efficiency and flexibility. It supports multiple AI models, provides code modification and model list functions, and integrates with Claude Code through the MCP protocol.

A simple server project that interacts with AI models of OpenAI and Claude as a master control program (MCP), providing a unified API interface and automatic provider detection function.

This is a generative AI course project for beginners, providing a complete learning path from environment setup to practical application. The project includes 6 concept courses and 6 programming courses, using the Azure OpenAI service for practical operations. Learners can quickly start through GitHub Codespaces or choose to install the Python environment locally. The project emphasizes the secure management of API keys and provides detailed setup guides. In addition, learners are encouraged to participate in open-source contributions, and an AI community communication platform is provided.