Recursive Language Model patterns for Claude Code — handle massive contexts (10M+ tokens) by treating them as external variables

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

APISIX Model Context Protocol (MCP) server is used to bridge large language models (LLMs) with the APISIX Admin API.

Collection of Claude Skills for DSPy framework - program language models, optimize prompts, and build RAG pipelines systematically

Recursive Language Models for Claude Code - Infinite memory solution inspired by MIT CSAIL paper

Chiasmus is an MCP server that gives language models access to formal verification

AI-powered reverse engineering assistant that bridges IDA Pro with language models through MCP.

📦 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

Rails Engine with MCP compliant Spec.

Your First LLM-Wiki Conversation Knowledge Base

Production Claude Code skills for n8n from a Verified Creator's 100+ workflows

OpenCode plugin: Ralph outer loop + RLM inner loop — iterative AI development with file-first discipline and sub-agent support

Observal is self-hosted registry for your coding agent extensions with a built in insight engine. Setup Observal, define the scope and share your Skills, MCPs and Agents with your peers.

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 autoresearch powered by autonomous coding agents. Run Claude Code, OpenCode, and Codex with grading, shared knowledge, and multi-agent evolution. Accepted at COLM 2026.

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.