Local-first persistent brain for AI coding agents - SQLite knowledge graph + replayable trajectories, queryable over MCP.
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Updated
Sep 17, 2026 - TypeScript
Local-first persistent brain for AI coding agents - SQLite knowledge graph + replayable trajectories, queryable over MCP.
A deterministic Windows AI agent that doesn't hallucinate actions. Features native UI Automation (no blind clicks), file rollbacks, and strict HITL security.
A Knowledge Graph-Infused RAG framework for multi-hop reasoning over Türkiye-related entities. It utilizes Neo4j for graph storage, Wikidata5M for structured data, and Ollama (Qwen 2.5) for agentic spreading activation to outperform traditional text-based RAG baselines.
Cross-tool memory for AI agents. Stitch context across Cursor, Claude Code, Codex, Gemini CLI, Windsurf, Copilot, and 9+ AI tools. Preserves decisions, failed experiments & warnings across sessions. Zero dependencies, MCP + instruction files, BM25 relevance search. Never re-explain your work.
Enable AI agents to share memory across tools and avoid repeating work when switching between tasks or platforms.
神农AI —— 基于 Neo4j AuraDB 云图数据库与 Agentic RAG 的中医药智能知识平台,收录 300+ 味常用药材,提供知识图谱可视化、药材管理、拍照识药、AI Agent问答、方剂推荐与配伍检测,实现可溯源RAG智能问答。
A hybrid search system for financial intelligence combining BM25, dense, and sparse vectors with Qdrant to improve retrieval across both exact keyword and semantic queries.
A RAG pipeline where an LLM agent chooses its own retrieval strategy through MCP, benchmarked against static baselines on 1,000 real biomedical questions.
Local-first knowledge retrieval engine for AI agents — BM25, semantic search, reranking, MCP, Pi Agent and DeepSeek Harness integration.
A privacy-first, self-hostable web search engine built from scratch in TypeScript — own crawler, own BM25 inverted index, zero cookies/tracking, and live hybrid fallback (Google Suggest + DuckDuckGo) when local results are thin.
Self-hosted AI search + chat platform that keeps LLM costs low: hybrid (BM25 + vector) search, RAG product chat, and rule-based query understanding that skips the LLM when it isn't needed. Works with OpenAI, Claude, Gemini, Groq, Ollama, or LiteLLM. Built on Typesense + FastAPI. ⭐ If you like this, please give it a star!
🧭 ПолиГид — единый цифровой навигатор Московского Политеха: сервисы, расписание, база регламентов и ИИ-поиск для студентов, абитуриентов и родителей.
A progressive materials-engineering RAG lab: dense retrieval, reranking, hybrid search, multi-query, decomposition, adaptive/corrective retrieval, and agentic R&D workflows with reproducible evaluation.
AI compliance assistant for gold-loan branch staff: cited answers from RBI regulations, in English and Hindi · RAG with BM25 + Groq · Streamlit
A local RAG assistant that will answer LLM security questions using retrieved OWASP documentation
Advanced conversational RAG assistant with Hybrid Search, BM25, RRF, Multi-Query Retrieval, Contextual Compression, Memory, Structured Output, Evaluation, and Streamlit UI.
AI-assisted job search backend that combines HH.ru filtering, semantic retrieval, BM25 ranking, LLM-based candidate evaluation, PostgreSQL caching, and cover letter generation.
A learning-focused Agentic RAG system built to explore LangGraph orchestration, hybrid retrieval, semantic caching, and RAG evaluation using local LLMs.
A local-first codebase context synthesizer. Uses AST parsing, DAG call-graph traversal, and BM25 search to pack token-budgeted context for LLMs.
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