AI memory system combining vector search with temporal knowledge graph. Built-in cognitive engine for agents. Supports memory decay, contradiction detection, and MCP integration.
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.
Evidence-first, multilingual, S3-native RAG — answers only from cited evidence (exact quote, page, bbox) and abstains when the evidence is weak, missing or conflicting. The guarantee is "no ungrounded claim". Byte-identical core across Python, Go and JavaScript. Docs: https://muthuishere.github.io/citenexus/
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.
Govern your documents like code. MCP server that indexes .md/.docx/.html/.pdf into a SQLite knowledge graph and runs drift audits — stale policies, conflicting research claims, superseded docs, undocumented code exports. 12 MCP tools incl. cross-reference graph, governance + provenance metadata, topic similarity. Single binary, zero runtime deps.
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
A team of specialized AI agents covering the complete software development flow — from requirements discovery to deploy. One responsibility per agent, specs as source of truth, no shortcuts.
Self-improving context & memory for Claude Code and OpenAI Codex. One canonical knowledge store injected only when relevant — hooks push budgeted context, an MCP server serves depth on demand, and it learns lessons from your sessions. Agent memory + context engineering as a single static Go binary.
Your agent's most expensive failure is not forgetting. It is confidently remembering the old answer. inspeximus retires a corrected fact by key, takes the correction back on command, and leaves a receipt you can verify. Long-term memory for AI agents: one zero-dependency Python file, MCP server for Claude Code, Cursor, Windsurf, Codex and Cline.
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.
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.