memanto
moorcheh-ai
Cross-agent memory layer with three verbs (remember, recall, answer) over an information-theoretic engine, no vector DB.
What is memanto?
An active-memory layer for AI coding agents that exposes three operations, remember, recall and answer, for persistent typed memory across sessions, with temporal queries and versioning. It is a client and CLI over 'Moorcheh', an information-theoretic semantic engine that runs locally via Docker/Ollama or as a hosted service, so no traditional vector database is required, and it connects to many agents via one command.
Pros & Cons
Pros
- Broad agent coverage via one connect command (Claude Code, Cursor, Codex, Windsurf, Cline and more)
- A local-first option (Docker, no API key, free tier), so you are not forced onto the cloud
- A simple three-verb API with typed categories plus temporal queries, versioning and conflict detection
Cons
- The core Moorcheh engine is proprietary, so the MIT licence covers only the client, not a fully open, auditable stack
- Comparative benchmark claims (LongMemEval, LoCoMo, versus Mem0/Zep/Letta) are self-reported and unverified
- Pre-1.0 (v0.2.x), so the API may change
License
MIT (OSI-open)
The memanto client is MIT (OSI-open); the core 'Moorcheh' semantic engine it depends on is proprietary (self-hosted via Docker or used as a cloud service), so the end-to-end stack is not fully open.
When it is interesting
You want a drop-in memory layer that works across many coding agents, locally or in the cloud, without standing up a vector database.
When it is too early
If you need a fully open-source, auditable memory stack or production stability.
Commercial alternative & related
- Commercial counterpart: Mem0
This repo featured in the 2026-07 edition of the Open-Source AI Radar.
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