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amem

by sslugic
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    • code-recall

      AbianS
      A
      license
      Not graded
      quality
      C
      maintenance
      Gives AI coding agents persistent memory by storing observations, decisions, and learnings in a local SQLite database with vector search, full-text search, and a rules engine.
      4
      MIT

    • Sugar

      rSenturk54927
      F
      license
      Not graded
      quality
      A
      maintenance
      Provides a local-first persistent memory layer that lets AI coding agents store, recall, and semantically search project-specific and cross-project knowledge across sessions, so context, decisions, and guidelines survive between conversations. Runs entirely on the user's machine with SQLite and no API keys, and optionally supports autonomous task-queue execution built on the same memory.
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    • Sugar

      dorothymartinez015
      F
      license
      Not graded
      quality
      A
      maintenance
      Provides a local-first, cross-session memory layer that lets AI coding agents store and semantically search per-project decisions, preferences, error patterns, and research alongside global guidelines. Also supports an optional task queue for autonomous execution, all backed by on-disk SQLite with no API keys or external calls.
      -

    • Sugar

      Alekseev3387
      F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding agents to store, search, and recall persistent project-specific and cross-project context — decisions, preferences, error patterns, and guidelines — from a local-first SQLite memory store with semantic search, so knowledge survives across sessions. An optional companion task server lets agents queue and autonomously execute work using that same memory.
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    • Sugar

      riyascholz4388
      F
      license
      Not graded
      quality
      A
      maintenance
      Gives AI coding agents a local-first persistent memory they can read and write directly during sessions, storing decisions, preferences, error patterns, and guidelines in per-project and global SQLite stores. Enables semantic and keyword retrieval of relevant context across sessions so agents start work already knowing a codebase's conventions and history.
      -
    Deploy Server
    Context All Your Agents Can ShareAgents share what they learn, hand off work, and hold it when you switch models. Start with 5 GB free.fulcradynamics.comAd

    TDQS

    A3.5/5.0

    Scored across 16 tools

    Disambiguation4/5

    Most tools target distinct actions or resources: memory retrieval, remembering, superseding, skills, tasks, and usage reporting are clearly separated. A few boundaries are softer, especially amem_context vs amem_graph vs amem_status and amem_stats vs amem_usage_report, but the descriptions largely clarify intended use.

    Naming Consistency3/5

    All tools share the amem_ prefix and snake_case, which helps. However, naming conventions are mixed: some use resource_action (amem_skill_view, amem_task_add), some are bare verbs (amem_remember, amem_supersede), and others are nouns or noun phrases (amem_context, amem_repos, amem_usage_report).

    Tool Count4/5

    At 16 tools, the set is slightly heavy but still within a reasonable range for a memory server with skills, tasks, inventory, and usage reporting. Each tool appears to have a real role, though some consolidation could make the surface lighter.

    Completeness4/5

    Core lifecycle operations are present: memory read/write/retire, skill list/view/save, task list/add/update/complete, and usage/stats reporting. Minor gaps exist around explicit deletion or unmonitoring, and skills/tasks lack full delete/update coverage, but most workflows are supported.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

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