AI Agent Builder
Twelve curated skills for shipping production AI agents — LangChain adapters, RAG memory, vector stores (Pinecone, local), embeddings pipelines, OpenAI Responses, and observability for agent stacks.
Included skills (12/12)
Production-ready AI agent orchestration platform with 66 specialized agents, 213 MCP tools, ReasoningBank learning memory, and autonomous multi-agent swarms. Built by @ruvnet with Claude Agent SDK, neural networks, memory persistence, GitHub integration,
LangChain.js adapters for Model Context Protocol (MCP)
MCP server providing AI agent observability — tracing, cost tracking, performance monitoring, and audit trails
Unified MCP server for multi-LLM consultation — registers tools from all available providers (Gemini, Codex, Ollama) behind runtime availability checks
Local and OpenAI embedding providers for documentation search — runs 100% offline by default
ChromaDB vector store adapter for semantic documentation search
Model Context Protocol (MCP) server for LightRAG - 30 fully working tools with complete RAG and Knowledge Graph integration
Local RAG MCP Server - Easy-to-setup document search with minimal configuration
Model Context Protocol server for Pinecone - enables AI assistants to interact with Pinecone indexes and documentation
Lightweight MCP server (Responses API core). OpenAI integration + web_search.
Project-local RAG memory MCP server — knowledge graph + multilingual vector + FTS5 in a single SQLite file. Per-project isolation, 30 MCP tools, codepoint-safe chunking (Korean/CJK/emoji).
LLM provider tool format adapter for MCP — supports OpenAI, Claude, Bedrock, Gemini, and Mistral