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Related Servers

Alternatives to ctxkeeper

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding assistants to persistently save, search, and restore project context across sessions, including decisions, progress, file caches, checkpoints, and channel-based memory. It supports git-aware organization, batch operations, and shared memory across parallel sessions.
      228 npm
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding agents to read and write persistent project-scoped and cross-project memory during sessions, using local semantic search to surface relevant decisions, preferences, error patterns, and guidelines across sessions. It also optionally exposes an autonomous task queue that draws on that same stored context.
      -
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding assistants to maintain persistent context across sessions by saving, searching, organizing, checkpointing, and restoring conversations, decisions, file content, and progress.
      228 npm
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Provides AI coding agents with a local-first persistent memory layer they can read and write during sessions, storing decisions, preferences, error patterns, and research per project or globally. Enables semantic and keyword search, formatted context recall, and cross-project guideline surfacing without API keys or cloud storage.
      -

    TDQS

    A3.7/5.0

    Scored across 8 tools

    Disambiguation4/5

    Most tools have distinct roles: remember/recall/forget form a clear memory lifecycle, todo manages a separate list, and log_work and status are unambiguous. project_brief and context_pack both return token-budgeted context, but their scopes (session-start overview vs question-specific excerpts) are described well enough to distinguish them.

    Naming Consistency3/5

    The set mixes simple verbs (remember, recall, forget), noun-like names (todo, status), and compound names (project_brief, log_work, context_pack). No single predictable convention is followed, though all names are readable and mostly snake_case.

    Tool Count5/5

    Eight tools is well-scoped for a project-context memory server, with each tool covering a distinct operation. There is no obvious bloat or missing essential capability at this count.

    Completeness4/5

    The surface covers memory creation, search, archival with restore, todos, work logs, briefs, status, and context packing, providing solid lifecycle coverage. Minor gaps exist, such as no direct memory-edit operation or bulk cleanup beyond archiving by ID.

    Maintenance

    ActivityMaintained
    ResponsivenessSyncing