brain-mcp and mind-mem
Both tools are competitors, offering similar functionalities for persistent memory and cognitive context in AI agents, using a comparable number of MCP tools and hybrid retrieval methods, but differing in specific features like contradiction-safety and co-retrieval graphs.
About brain-mcp
mordechaipotash/brain-mcp
Your AI has amnesia. Persistent memory and cognitive context for AI. 25 MCP tools. 12ms recall.
Implements a progressive capability model—basic keyword search on raw conversations, semantic search with embeddings, and full domain reconstruction with AI-generated summaries—enabling AI assistants to surface cognitive patterns, unfinished threads, and evolved thinking across fragmented conversation histories from multiple tools (Claude, ChatGPT, Cursor). Operates as an MCP server exposing 25 specialized tools including semantic and keyword search, "prosthetic" functions like `tunnel_state` and `context_recovery` for domain re-entry, and analytics for identifying dormant contexts and thinking trajectories without requiring manual tagging.
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.
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