rms-memory-mcp — alternative #1 to cogmemai-mcp
🦀 🏠 🍎 🐧 🪟 - Local-first persistent memory for AI coding agents. Hybrid vector + full-text search (LanceDB + Tantivy), separate Markdown and...
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Recorded alternatives
Every candidate below sits in AI. What ends up on this page is decided entirely by a recorded score — not by bidding, not by editor taste. Review both records, check current vendor terms, then decide.
🦀 🏠 🍎 🐧 🪟 - Local-first persistent memory for AI coding agents. Hybrid vector + full-text search (LanceDB + Tantivy), separate Markdown and...
🐍 🏠 🍎 🪟 🐧 - Persistent memory for AI coding agents with semantic search, auto-capture, cross-session learning, and intelligent forgetting. 2...
🐍 🏠 🍎 🪟 🐧 - Persistent memory for AI agents with sectioned entries (project/user/context/etc), semantic search, CLI, and per-project scope....
Local-first multimodal video indexing and semantic search toolkit with transcript extraction, embeddings, scene-aware search. Can be used as...
📇 🏠 - First & only persistent project context MCP. Provides .faf (Foundational AI-context Format) Project DNA with 33+ tools, Podium scoring...
🐍 🏠 - Cognitive memory for AI agents with Atkinson-Shiffrin memory model (STM/LTM/sensory register), semantic RAG, Ebbinghaus decay, trust s...
Each candidate is a live catalogue record in the same primary category, picked by a deterministic score that Oryxen records in its catalogue: how many meaningful words the two listings share, whether their pricing classes oppose (a paid product against a free one), whether both are open source, and whether either record is featured. The same catalogue state always produces the same list — no randomness, no manual ranking.
No. Rows are ordered only by the recorded score, highest first, with alphabetical ties — payment never influences the order, nothing here is paid placement, and Oryxen charges no listing or placement fee.
Always verify current terms with cogmemai-mcp directly — Oryxen records pricing classes, not live quotes.