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Alternatives to hive-memory

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    Related Servers

    • F
      license
      A
      quality
      B
      maintenance
      Shared fleet memory for AI agents — what one agent learns, the whole fleet knows. Nightly self-correction: stale facts rewritten in place, duplicates merged. Recall pushed into every prompt in supported coding agents. Self-hosted.
      11
      3
      -
    • A
      license
      Not graded
      quality
      A
      maintenance
      Provides persistent memory for AI agents via MCP, enabling agents to store and access notes, files, and session context across sessions and clients while under user control.
      4
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to store, search, assemble, and manage local-first memories through seven MCP tools, including conversation turns, feedback, status, and dashboard access without cloud dependencies.
      AGPL 3.0
    • A
      license
      C
      quality
      A
      maintenance
      Provides AI agents with a human-inspired memory layer via MCP, enabling episodic and semantic memory recall, forgetting curves, consolidation, and contradiction detection. It integrates with MCP clients to offer local-first, dependency-free memory management.
      98
      1
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables MCP-compatible coding tools to share a portable, local-first AI work identity and memory layer, so preferences, decisions, lessons, and project context persist across sessions and clients. Users can inspect, edit, approve, and override what the AI receives, keeping the store on their own machine without a cloud account.
      -
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables multiple AI agents and clients to share a self-hosted memory store over MCP or REST, supporting note creation, search, change tracking, and optional semantic retrieval from desktop, web, or mobile.
      MIT

    TDQS

    A4.5/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool has a clearly delineated role, and the descriptions actively resolve boundary cases (recall vs get_context vs manage list_pending; say vs board; propose vs manage). No two tools compete for the same action, so misselection is unlikely.

    Naming Consistency4/5

    Names are uniformly short and lowercase, but the style is slightly mixed: mostly bare verbs (recall, propose, manage, say) alongside a verb_noun (get_context) and a bare noun (board). It remains readable and predictable in tone, just not a strict single pattern.

    Tool Count5/5

    Six tools cleanly cover the memory lifecycle plus agent communication, with no redundant or filler entries. Each tool earns its place for a focused memory server.

    Completeness4/5

    Full read/create/pending-inspect/soft-delete/restore lifecycle is present, plus session bootstrap and a messaging channel; no dead ends in the core flow. The one visible gap is revising the content of an already-confirmed memory (only forget/restore, not edit), which agents must work around via propose.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues