mind-mem and memorix
These two tools are competitors, with AVIDS2/memorix focusing on cross-IDE memory persistence via MCP and broader team collaboration, while star-ga/mind-mem offers persistent, auditable, and contradiction-safe memory for coding agents using a hybrid BM25 + vector retrieval approach with MIND-accelerated scoring and a narrower set of 19 MCP tools.
About mind-mem
star-ga/mind-mem
Persistent, auditable, contradiction-safe memory for coding agents. Hybrid BM25 + vector retrieval, 19 MCP tools, co-retrieval graph, MIND-accelerated scoring. Zero external dependencies.
Implements shared memory across all MCP-compatible AI agents (Claude Code, Cursor, Windsurf, etc.) via a single SQLite workspace with concurrent-safe WAL mode. Core architecture combines BM25F full-text + vector retrieval with RRF fusion and intent-aware routing, plus a co-retrieval graph using PageRank-style propagation to surface structurally-related blocks. Includes active contradiction detection, drift analysis, and deterministic governance—all Markdown-backed with full audit trails and zero external dependencies.
About memorix
AVIDS2/memorix
Cross-Agent Memory Bridge Persistent memory for AI coding agents across 10 IDEs (Cursor, Windsurf, Claude Code, Codex, Copilot, Kiro, Antigravity, OpenCode, Trae, Gemini CLI) via MCP. Team collaboration, auto-cleanup, mini-skills, workspace sync. Never re-explain your project again.
This project gives AI coding agents a shared, persistent memory that goes beyond a single conversation or IDE. It helps developers and engineering teams using multiple AI coding agents like GitHub Copilot or Gemini CLI by allowing agents to remember past project details, decisions, and reasoning across different sessions and development environments. The result is that you don't have to re-explain your project to your AI assistant repeatedly.
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