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Related Servers

Alternatives to global-memory

No user-submitted related servers found.

    Related Servers

    • -
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables AI assistants to maintain persistent conversations and context between sessions through automated saving and global installation across projects. Provides zero-configuration memory persistence with automatic conversation history preservation.
      -
    • A
      license
      A
      quality
      A
      maintenance
      Provides persistent memory for AI assistants like Claude, enabling them to remember user identity, projects, and conversations across sessions and platforms via natural language commands.
      29
      408 npm
      2
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI assistants to retain persistent, searchable memory and versioned vaults, spawn and recall named agents with state and audit history, run automations, monitors, and deep research, and execute on-chain and web tasks across sessions. It can be installed alongside Claude Code, Cursor, Windsurf, Zed, Hermes, and other MCP clients, with vault and memory optionally run entirely on the user's machine.
      45
      21 npm
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Living memory for AI coding agents (Claude Code, Cursor, Copilot, Codex). Cross-vendor persistent memory, decision recall, and outcome calibration via MCP and hooks.
      780 npm
      Apache 2.0

    TDQS

    A3.8/5.0

    Scored across 9 tools

    Disambiguation4/5

    Most tools have clearly distinct roles: recall/record_usage, list/overview, and start_consolidation/apply_consolidation are well separated. The only potential confusion is between update_memory and apply_consolidation (both can modify presets) and between delete_memory and apply_consolidation's delete, but the usage context (direct user action vs. consolidation workflow) disambiguates them.

    Naming Consistency4/5

    Eight of nine tools follow a consistent verb_noun pattern (record_usage, list_memories, update_memory, start_consolidation, apply_consolidation, recall_presets, save_requirement, delete_memory). memory_overview breaks the pattern by being noun_noun, but it is still readable and clearly the odd one out.

    Tool Count5/5

    Nine tools is a well-scoped size for a memory/preset management server. Each tool covers a distinct operation or workflow stage—CRUD, recall, usage reporting, and consolidation—without redundancy or bloat.

    Completeness5/5

    The tool surface covers the full lifecycle: save_requirement creates presets, list_memories/memory_overview/recall_presets read them, update_memory plus apply_consolidation handle updates/disable/archive, and delete_memory covers deletion. The two-phase consolidation workflow and record_usage for outcome tracking round out the domain with no obvious gaps.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues