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Alternatives to raggy-mcp

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    Related Servers

    • A
      license
      Not graded
      quality
      D
      maintenance
      Provides persistent knowledge graph memory for AI agents, enabling them to store, recall, and query facts about people, projects, and relationships across sessions.
      MIT
    • A
      license
      A
      quality
      D
      maintenance
      Provides persistent long-term memory for AI agents through semantic search and automated knowledge graph extraction. It enables agents to store, recall, and reason over facts, preferences, and relationships across multiple conversations and sessions.
      14
      14 npm
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    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables persistent, graph-based memory for AI agents, allowing them to store, traverse, and recall relationships between facts, decisions, and context across sessions for efficient reasoning and reduced token usage.
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Provides long-term memory and a temporal knowledge graph for AI agents, enabling persistent memory and reasoning across sessions.
      33
      52 PyPI
      2
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Provides persistent, cross-session memory for AI agents, allowing them to store and automatically retrieve information across different conversations and sessions without repeating context.
      9 npm
      175
      MIT

    TDQS

    A4/5.0

    Scored across 11 tools

    Disambiguation4/5

    Tools are largely distinct, but raggy_remember and raggy_capture both create memories, and raggy_context and raggy_recall both handle memory retrieval. Descriptions do separate them well via structured vs unstructured capture and session-start vs targeted lookup, so confusion is unlikely in practice.

    Naming Consistency3/5

    All tools share the raggy_ prefix and snake_case formatting, but naming style is mixed: upload, remember, capture, recall, forget, and link are verbs, while context, timeline, threads, and private_sources are noun phrases. There is no consistent verb_noun pattern.

    Tool Count5/5

    11 tools is well-scoped for a memory/knowledge server covering ingestion, retrieval, deletion, graph linking, and session introspection. Each tool has a clear role and the count feels appropriate rather than bloated or thin.

    Completeness4/5

    The set covers upload/list/delete for private sources, capture/remember/forget for memories, context/recall/timeline/threads for retrieval, and link for graph relationships. The main gap is no explicit update/edit operation for a memory, though supersedes links and forget redaction partially address that.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues