#rag

Persistent memory & code intelligence server for AI coding agents. Deploy on VPS for shared memory across machines. Hybrid search (BM25 + pgvector), knowledge graph, impact analysis. 14 MCP tools. Works with Claude Code, OpenCode, Cursor, and any MCP client.

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.

Persistent memory MCP server for AI agents — Rust, 19 tools, knowledge graph, Hebbian learning, episodic memory, contradiction detection, prospective triggers, Bayesian calibration, zero-config Docker setup.

Self-evolving skills lib for coding agents

🐙 Drop-in tools that give AI agents reliable, permission-aware access to external systems.

CLI tool for building production RAG systems from Markdown, CSV, and PDF documents using hybrid search (BM25 + vector) with OpenSearch. Features MCP server, Slack bot, Web UI, multi-source ingestion (local/S3/GitHub), and multi-provider embeddings (Bedrock/Gemini).

A modern Go framework for building multi-agent AI systems.

Local-first shared memory for Claude Code, Codex, OpenCode, Kimi, Grok, Cowork, and Hermes, with bounded observation and searchable Markdown context.

Kreuzberg v4 LTS — long-term support for the v4 line (legacy; superseded by xberg for v5+). MIT-licensed.

Git-anchored decentralised intent(conversation) ledger for teams who build with AI

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.

Self-hosted AI memory engine - Ebbinghaus forgetting-curve decay, interaction-aware reinforcement, and conscious thought synthesis. Local SQLite + sentence-transformers embeddings.

No repository description published.

OpenCodeRAG is a RAG (Retrieval-Augmented Generation) plugin for semantic code search powered by locally-hosted embedding models. It features a seamless integration with OpenCode and offers a CLI interface for external usage.

An agent framework for Go with graph-aware memory, UTCP-native tools, and multi-agent orchestration. Built for production.

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

AI memory system combining vector search with temporal knowledge graph. Built-in cognitive engine for agents. Supports memory decay, contradiction detection, and MCP integration.

Zero-config NL-to-SQL data engine with multi-tenant isolation, built for embedding in multi-tenant SaaS apps.

AI agent that lives in your chat apps. Controls your machine, remembers your conversations, searches your documents — with guardrails so it doesn't go rogue. OpenClaw without the bloat

一个本地优先的AI知识库系统（RAG），用于把本地文档接入辅导搜索与大模型对话流程。目前支持md、txt、pdf（文本）、xlsx、cvs类型。支持mcp服务

Local‑first MCP server for multi‑repository semantic code search with Qdrant and llama. Turns your entire workspace into private context for AI coding assistants like Claude Code, Codex, Cursor, Copilot, Antigravity and Windsurf.

Semantic code search for coding agents — search by meaning like grep, trace call graphs, find tests & blast radius. 100% local embeddings (ONNX/MLX), MCP server, plugins for Claude Code, OpenCode, Codex & Droid.

Local-first dynamic memory for agents and apps: SQLite source of truth, vector search candidates, hotness, decay, TTL, namespaces, and benchmarks.

An agent framework for Go with graph-aware memory, UTCP-native tools, and multi-agent orchestration. Built for production.

Turn YouTube, websites, and arXiv papers into a structured, reusable corpus of insights, syntheses, and reports.

No repository description published.

An agent framework for Go with graph-aware memory, UTCP-native tools, and multi-agent orchestration. Built for production.

An open source deterministic or LLM-enhanced agent showcasing and implementing the KCP protocol

GoRAG is a production-ready, high-performance RAG (Retrieval-Augmented Generation) framework built entirely in Go. Designed for enterprise scalability, it seamlessly connects your internal data to the most powerful LLMs with zero Python dependencies.

Create conversational AI solutions with custom data and abilities using ChatBotKit for Go applications.