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    • -
      license
      Not graded
      quality
      Not graded
      maintenance
      Provides persistent local memory functionality for AI assistants, enabling them to store, retrieve, and search contextual information across conversations with SQLite-based full-text search. All data stays private on your machine while dramatically improving context retention and personalized assistance.
      3
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to save, recall, and forget persistent memories stored entirely on the local machine in SQLite, using hybrid semantic and keyword search with on-device embeddings, plus spaces and profile context injection.
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Gives AI agents persistent, local-first memory using SQLite and on-device embeddings, enabling semantic search and recall across sessions with no cloud calls.
      8
      9
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Gives every AI agent you use one shared, versioned memory in a local SQLite file, so a fact saved from one app is found by all the others. Runs fully offline with no API key, records which agent wrote each change, and keeps every prior version so nothing is silently overwritten.
      7
      964 npm
      8
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Provides persistent long-term memory for LLMs via local SQLite storage and semantic search, enabling recall across sessions without external APIs.
      15 npm
      5
      MIT
    • A
      license
      Not graded
      quality
      B
      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

    TDQS

    A3.7/5.0

    Scored across 10 tools

    Disambiguation3/5

    The memory CRUD tools (remember, recall, recall_full, forget, recent) are clearly separable, but handoff and whats_up overlap heavily: both instruct the agent to 'call this FIRST when you start work in a project' and both return the last session's notes (decided/done/next/open). Only the live-state extras distinguish whats_up, so an agent may pick either or both. recall vs search_chats is a milder overlap (stored memory vs past chat excerpts) but the descriptions do enough to separate them.

    Naming Consistency3/5

    Mostly snake_case, but conventions are mixed: bare verbs (remember, recall, forget), a noun/adverb (recent, handoff, whats_up), a qualified variant (recall_full), and a prefixed pair (access_status/access_change). It is readable and nothing is cryptic, but there is no single predictable verb_noun pattern across the set.

    Tool Count5/5

    Ten tools is a well-scoped surface for a personal memory/context server: five cover memory lifecycle, one covers chat history, two cover project continuity, and two cover access control. Each tool has a defensible place with no filler.

    Completeness4/5

    Core lifecycle is covered: write (remember, which also updates near-duplicates), read/search (recall, recall_full, recent), delete (forget), plus chat search, project continuity, and read/write access control. Minor gaps exist: no explicit edit/append to an existing memory id, no list of sections/tags or bulk export, and the restore path for forgotten memories is described but not exposed as a tool.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues