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    Related Servers

    • F
      license
      Not graded
      quality
      B
      maintenance
      Local-first memory for AI coding agents. Indexes your Claude Code, Codex, Cursor, Cline and Gemini CLI history by repo/branch/worktree and hands a context capsule (decisions, touched files, next steps) to the next agent over MCP.
      -
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding agents to store, search, and retrieve persistent local-first memory — project-specific decisions, preferences, error patterns, and research plus cross-project guidelines — so context survives across sessions without any external API calls. Optionally also exposes a task queue for autonomous execution and GitHub issue resolution in MCP clients such as Claude Code, OpenCode, and Goose.
      -
    • A
      license
      A
      quality
      A
      maintenance
      Semantic codebase search + persistent working memory for AI code editors. Local, zero-config, MCP. No API key.
      23
      2
      MIT
    • A
      license
      B
      quality
      A
      maintenance
      Local-first, auditable memory for Codex, Claude Code, and MCP clients. It stores scoped user/project memory in SQLite or Postgres, serves read-only recall and inspection tools by default, and supports opt-in governed writeback with review and forget controls.
      8
      183 npm
      20
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Shared, local memory for AI coding tools that stays true to your code. Claude Code, Cursor, and Codex share one memory per project; memories are linked to the files they depend on and retired automatically when those files change. Includes a local dashboard, import from CLAUDE.md/AGENTS.md, and export. Runs entirely on your machine.
      10
      163 PyPI
      3
      MIT

    TDQS

    A3.9/5.0

    Scored across 17 tools

    Disambiguation4/5

    Most tools have clearly distinct purposes—search, list, count, drill-down, and work-item aggregation are separated well. The main overlaps are get_related_activities vs get_work_item, and search_activities vs semantic_search_activities, but the descriptions provide enough guidance to choose correctly.

    Naming Consistency4/5

    The core set follows a consistent verb_noun snake_case pattern like list_activities, count_activities, and resolve_person. A few names deviate—who_worked_on, recent_decisions, current_time, and the abbreviated prep_meeting—but the overall style remains readable and predictable.

    Tool Count4/5

    At 17 tools, this is slightly above the ideal 3-15 range, but the server covers a broad domain spanning activity search, work items, people, summaries, and meeting prep. Most tools earn their place and support distinct workflows rather than padding the surface.

    Completeness4/5

    The read/query surface is strong: search, list, count, drill-down, person resolution, work-item aggregation, and pre-built summaries cover the main recall workflows. The notable gap is that log_event supports creating manual notes but there is no update or delete path, and there is no explicit metadata tool for enumerating sources or types.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues