#rag

Self-hosted retrieval infrastructure for AI assistants. MCP-first search and grounded answers over a private corpus, with citations that resolve to a real location in a real document — a page, a heading, a line, a cell.

Local MCP server that helps coding agents stop re-reading the same code every turn. Repository intelligence, cache-write optimization, and long-term session memory. 100% local. No API keys.

Code search that lets AI coding agents find the right files in fewer steps. Use the hosted endpoint or self-host, works with Claude Code, Copilot and Cursor via MCP.

saige - Super Artificial Intelligence Graph Environment. A unified Go SDK, CLI, and MCP server for streaming AI agents, knowledge graphs, and RAG pipelines, with Ollama, OpenAI, Anthropic, and Google providers behind one interface.

The RAG pipeline that grows with your codebase — index once, stay in sync with every commit.

🌿 Production-grade Go framework for conversational AI agents — LLM abstraction, RAG, memory, WhatsApp, scheduling & observability built in.

The self-correcting memory layer for AI agents. Zero-dependency Python memory and MCP server. Supersede, revert, or forget a value deterministically. Verifiable erasure, witness-backed tamper-evident receipts, EU AI Act ready.

AI-Lake Format: self-contained Parquet + HNSW index — unifying tabular data, embeddings, and vector search in a single Iceberg-compatible file

Open-source AI customer support system. AI-first support, human-ready operations.

Production-ready .NET 10 RAG library with hybrid vector + keyword search, multi-backend storage (SQLite, PostgreSQL, Neo4j, Qdrant), and MCP server integration.

Orquestador multi-agente de CLIs de IA para pipelines RAG

Bitemporal memory for AI agents: deterministic contradiction resolution, provenance, and retrieval at any point in time.

Local, privacy-first RAG memory system for Claude Code

Local code search for AI agents: six fast, purpose-built tools that return ranked answers, not raw grep. Because maybe grep isn't all you need... 🍬

RushDB is a graph + vector database and memory layer for AI agents. Push any JSON, get typed, searchable, relationship-aware records back — no schema, no migrations. Built on Neo4j.

A lightweight, high-performance AI/RAG workspace and autonomous agent framework implemented in Go. Inspired by the Leann RAG backend architecture

Typed building blocks for everything around your LLM call.

Rust-based FAST local markdown search engine (with possible support for CJK)

53AI Hub is an open-source AI portal and knowledge base for managing enterprise knowledge, AI agents, prompts, and AI tools, seamlessly integrating with Coze, Dify, FastGPT, RAGFlow. 一个AI知识库与Agent门户

Production-grade Go SDK for building AI agents with long-term memory, knowledge retrieval, and voice — runnable as a library, a daemon, or a real-time pipeline.

Open-source Go agent runtime for autonomous AI systems and multi-agent automation. MCP, RAG, 15+ LLM providers and 60+ built-in tools in a single binary.

ID-based RAG FastAPI: Integration with Langchain and PostgreSQL/pgvector

Open-source Java/SpringAI/Spring Boot AI enablement/orchestration layer for applications with RAG, governed actions, providers, vector stores, PII, tenant safety, chat memory, and behavior analysis.

Local-first private AI memory layer / Digital Brain for conversations, documents, decisions, and model-agnostic knowledge.

Lightweight HTML-to-Markdown parser for AI agent workflows — Python CLI and API around a fast Go engine, available on PyPI.

A framework for Forward Deployed Engineers: from problem statement to a deployable AI project — every decision traced to a fact, every fact to a source.

Graph memory for AI agents: facts in, entities and cause->effect relations extracted with small open models, multi-hop recall with a cited chain. Library, HTTP/MCP service, LangChain, hosted at memory.primaxiom.ai

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Find out what your coding agents already know. Docmancer indexes the memory, rules, and instructions Claude Code, Codex, Cursor, and Gemini wrote on your machine, then carries the durable parts to every agent. It is local-first and under MIT license.

Kura — the knowledgebase for humans and agents. Agent-native docs infrastructure, built on June.