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Alternatives to lean-memory

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    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Local memory for AI agents in one SQLite file on your own machine. Facts carry a validity window and a confidence score, so an outdated one is superseded and downweighted rather than deleted, and retrieval fuses BM25, vector similarity and a knowledge graph.
      2
      Business Source 1.1
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to keep durable long-term memory on the user's own machine, writing sessions and messages into a local SQLite database and retrieving them via keyword, exact, or optional semantic search with surrounding context. Runs entirely offline over stdio, so no cloud service or API key is required to give an agent recall across sessions.
      1
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Persistent semantic memory for AI agents. SQLite-backed, local-first, zero config. Semantic search via Ollama embeddings with keyword fallback. Tools: remember, recall, history, forget, stats.
      17
      37 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Lightweight persistent memory for AI agents using a single SQLite file with hybrid search (keywords + semantics). Zero to 12MB install, no cloud or server required.
      6
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents and any MCP-compatible client to persist, search, update, and delete plain-text memories across sessions, using BM25 lexical ranking over SQLite FTS5 with namespace filtering, tags, free-form metadata, and JSONL export/import — entirely local, with zero external infrastructure.
      MIT

    TDQS

    A4.5/5.0

    Scored across 7 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: add, search, clear, maintenance status, maintenance run, review queue, and review decide. There is no overlap or ambiguity between them.

    Naming Consistency4/5

    All tools use the 'memory_' prefix and lowercase with underscores. Most follow a verb-noun pattern (memory_add, memory_search, memory_clear, memory_maintenance_run, memory_review_decide), though memory_maintenance_status uses a noun phrase and memory_review_queue is ambiguous. Overall the pattern is predictable.

    Tool Count5/5

    Seven tools is well-scoped for a memory management server, covering ingestion, retrieval, deletion, and maintenance workflows without redundancy. Each tool earns its place.

    Completeness4/5

    The set covers the main CRUD-like operations (add, search, clear) plus a full maintenance lifecycle (status, run, review queue, decide). Minor gaps exist: no direct list-all-facts operation and no per-fact deletion, but these are noted as design limitations and do not severely hinder agent workflows.

    Maintenance

    ActivityStale
    ResponsivenessUnresponsive