Skip to main content
Glama
hexingyuofficial

style-memory-mcp

Official

Related Servers

Alternatives to style-memory-mcp

No user-submitted related servers found.

    Related Servers

    • F
      license
      Not graded
      quality
      D
      maintenance
      A local-first MCP server that builds compact voice profiles from writing samples, then compares, rewrites, or generates new text in that voice.
      -
    • A
      license
      A
      quality
      B
      maintenance
      A local, user-owned memory MCP server that allows AI agents to share context via a SQLite file you own.
      4
      MIT
    • F
      license
      B
      quality
      B
      maintenance
      MCP server that bridges multiple AI agents for unified local chat, supporting private messages, chat rooms, role queues, and broadcast with fixed identities and rate limiting.
      14
      1
      -
    • A
      license
      Not graded
      quality
      D
      maintenance
      A private, local-first MCP server that gives any AI long-term memory — its own diary. Zero models, zero network, zero subscription; smarter search than Notion, running entirely on your machine.
      MIT

    TDQS

    A3.8/5.0

    Scored across 15 tools

    Disambiguation5/5

    Each tool targets a distinct operation or resource (e.g., distill, forget, list, pin, review) with clear separation between interaction preferences and style habits. No two tools have overlapping purposes.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern using snake_case, such as distill_interaction_profile, forget_style_habit, and list_style_habits. The naming is predictable and uniform.

    Tool Count5/5

    15 tools is well-scoped for the domain of style and preference memory management, covering learning, retrieval, modification, review, and control without being excessive or insufficient.

    Completeness4/5

    The surface covers observation, distillation, retrieval, forgetting, pinning, reviewing, and toggling learning. Minor gaps include lack of manual creation or editing of individual preferences, but the learning-focused design justifies this.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues