Explore live open-source projects and AI models.

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-ste... Read more

Open-source metasearch backend, MCP server, and AI search API for LLM agents. Python FastAPI search gateway with Google search via SerpBase and Serper, multi-engine search aggregation, structured JSON output, provider fallback, deduplication, and SearXNG alternative architecture for agent workflows.

AI Agent 面试知识库：覆盖 LLM、Prompt、RAG、MCP、Tool Use、Agent 架构、Multi-Agent、LangGraph、Claude Code、Codex CLI、工程化评估、安全与源码解析。

Privacy-first semantic code navigation MCP server using RAG. Features deep AST multi-language support (Go, PHP/Laravel/WP, JS/TS/React, Python), 100% local LLMs (Ollama), and vector search (Qdrant) for AI IDEs like Cursor, Windsurf, Copilot, and Claude.

Open-source AI Agent platform — 80+ MCP tools, 7 channels (Slack/Discord/LINE/Telegram), Rust + Python. Self-hostable Claude/GPT alternative for production multi-LLM systems.

Felix — single-binary AI agent gateway. Multi-provider LLM, persistent memory, MCP client, runs entirely on your hardware

把多模型 Provider、本地密钥和 HeavySkill 讨论统一成 MCP 网关 | Local MCP gateway for multi-provider LLM routing, secrets, and HeavySkill discussions.

Wavelet-based multi-resolution context management for LLMs via MCP

Production-grade multi-agent orchestration engine. Compose agentic workflows from a pluggable catalog of Agents, LLMs, tools, and retrievers. Execute locally with LangGraph or distributed with Temporal. Built-in RAG pipeline for enterprise knowledge retrieval. A2A and MCP protocol support. Visual... Read more

MindBridge is an AI orchestration MCP server that lets any app talk to any LLM — OpenAI, Anthropic, DeepSeek, Ollama, and more — through a single unified API. Route queries, compare models, get second opinions, and build smarter multi-LLM workflows.