Yorishiro: Extract character souls from films/novels, generate SOUL.md for AI roleplay. Dual-layer memory (SOUL.md + RAG), knowledge boundary filtering, split-persona support, MCP-ready. Works with cloud or local models.

Intelligent context management for AI coding assistants. Indexes your codebase with tree-sitter, builds a semantic knowledge graph, and serves 12 tools over MCP. Hybrid RAG combines keyword search, vector embeddings, and graph traversal for precise retrieval. Works with Claude Desktop, Cursor, and any MCP client. Fully local with Ollama.

A semantic search and retrieval system for local documents using vector embeddings. Powered by MCP (Model Context Protocol).

All-in-one AI chat studio — 7 providers (Ollama, Claude, OpenAI, vLLM, Claude Code, Codex, Gemini CLI), RAG knowledge base, MCP tool integration, Mem0 shared memory, and 3-step pipeline. 100% local-capable. MIT licensed.

Easy RAG scripts for a local, embedded, MCP-enabled knowledge store.

KnowledgeBase MCP is a lightweight, containerized solution that creates a queryable, self-updating knowledge base from your local documents, focusing on efficient retrieval for RAG applications.

Production ready LangGraph multi-agent orchestration template with supervisor routing, FastAPI + Streamlit chat UI, MCP tool calling, local RAG + knowledge graph retrieval, PostgreSQL memory, per-user auth, and CI/CD.

A Docker-based RAG server that transforms your Obsidian vault into an intelligent, personal knowledge base. 🧠 Enables powerful semantic search on your notes, acting as a secure, local MCP tool for the Gemini CLI.

A fully local RAG-based knowledge base system with an MCP (Model Context Protocol) server. It enables document upload and search through AI assistants using MCP, while guaranteeing that all documents and embeddings remain local with zero external data exposure.

Production-grade Graph-RAG MCP server with local embeddings — persistent knowledge graphs for any LLM-powered CLI agent

Persistent AI memory without RAG — agent-navigated local knowledge base via MCP. Works with Claude Desktop, LM Studio, and ChatGPT.

Retrieval-Augmented Generation (RAG) server that seamlessly integrates with Claude Desktop through the Model Context Protocol (MCP). This project enhances Claude's capabilities by providing access to your local document knowledge base through an advanced RAG pipeline.

Math Routing Agent is an Agentic-RAG system that acts as an AI-powered mathematics professor. It intelligently routes math queries between a local knowledge base and live web search, ensuring accurate and up-to-date answers. Equipped with AI guardrails, human-in-the-loop feedback, and structured context (MCP)

Prometheus Knowledge System — RAG local BM25+embeddings MCP server

100% offline RAG storage and MCP server for querying local document knowledge bases

MCP server for project-local RAG memory with knowledge graph and multilingual vector search

MCP server for RAG knowledge base search — local embeddings (fastembed/ONNX) + vector search (LanceDB)

Local-first loop/task and knowledge assistant with web UI, CLI, FastAPI, SQLite RAG, and an MCP server.

Industrial-grade Local AI Coding Agent with MCP tools, RAG knowledge, Skill memory, autonomous execution loop and Docker deployment.

Local RAG System with MCP Server A production-grade Retrieval Augmented Generation (RAG) system with Model Context Protocol (MCP) server integration, built for intelligent document querying and developer knowledge management.

an ai agent built based on mcp server(function calling) and rag(local knowledge base) which has the memorizing ability

A Model Context Protocol (MCP) server that implements Retrieval-Augmented Generation (RAG) capabilities with local embeddings and persistent knowledge storage using ChromaDB.

MCP RAG server — local embeddings, your docs never leave your machine. Private knowledge base + web search for Claude, Cursor, and Ollama. Drop your docs, connect your AI client, done.

A local, privacy-first AI knowledge base. Index documents, websites, and GitHub repos — then ask questions and get accurate, sourced answers powered by local LLMs. Desktop app (Electron) + RAG backend (FastAPI/Qdrant) + MCP server. Everything runs on your machine.

EgoVault is a local knowledge pipeline. Ingest videos, YouTube links, audio, PDFs, and ideas into a structured vault. Browse it in Obsidian. Query it with any LLM via MCP with targeted RAG (semantic similarity).

All-in-one offensive security toolbox with AI agent and MCP architecture. Integrates tools like Nmap, Metasploit, FFUF, SQLMap. Enables pentesting, bug bounty hunting, threat hunting, and reporting. RAG-based responses with local knowledge base support.

A document Q&A system with a high-performance C++ text chunker, a local RAG pipeline with source attribution, and an MCP-compliant server that exposes the knowledge base as discoverable tools for any LLM client.