MCP server that enables language models to interact with RDKit through natural language

📦 Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. Perfect for when you need to feed your codebase to Large Language Models (LLMs) or other AI tools like Claude, ChatGPT, DeepSeek, Perplexity, Gemini, Gemma, Llama, Grok, and more.

The Model Context Protocol (MCP) is an open-source implementation that bridges Jenkins with AI language models following Anthropic's MCP specification. This project enables secure, contextual AI interactions with Jenkins tools while maintaining data privacy and security.

A Model Context Protocol (MCP) server that provides file system context to Large Language Models (LLMs). This server enables LLMs to read, search, and analyze code files with advanced caching and real-time file watching capabilities.

Wwise-MCP is a Model Context Protocol (MCP) server that enables large language models (LLMs) to interact with the Wwise Authoring application. It exposes a set of tools built on a custom Python WAAPI library, allowing MCP clients such as Claude or Cursor to automate and compose complex, multi-step Wwise workflows.

SkillX: Automatically Constructing Skill Knowledge Bases for Agents

A linguistic linter for Traditional Chinese (zh-TW)

[ICML 2026] Meta Context Engineering via Agentic Skill Evolution

Build and run agents you can see, understand and trust.

Learn AI and LLMs from scratch using free resources

Your First LLM-Wiki Conversation Knowledge Base

High-performance OpenAI and Anthropic compatible LLM inference server for Apple Silicon. Native MLX, continuous batching, multimodal models, MCP tool calling, and Claude Code support.

Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.

Bilingual (中文+EN) ML / LLM / diffusion / agent interview cheat sheets for AI 秋招 — generated by ARIS /interview-cheatsheet, rendered by /render-html into single-file HTML, reads anywhere — plus a CV→DBLP-fact-checked academic homepage generator and hand-authored long-form blogs 🌱

The Swiss Army Knife of Offline AI. Chat, see, speak, and generate images on your phone or Mac — GGUF LLMs, vision, Whisper speech-to-text, Stable Diffusion, tool calling, and local-network servers. Runs on your CPU, GPU, or NPU. No account, no API key, zero data leaves your device.