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Alternatives to Keel

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    Related Servers

    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to store and retrieve provenance-aware facts with source, age, and boundaries, supporting search, read, propose, and local telemetry via MCP tools.
      4
      81 npm
      Apache 2.0
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables AI agents to manage and query a temporally-aware knowledge graph memory, supporting episode tracking, entity relationships, and semantic search via MCP tools.
      1
      -
    • A
      license
      Not graded
      quality
      D
      maintenance
      Provides AI agents with operational customer context, including typed revenue objects, persistent state, scoped tools, and human-in-the-loop handoffs through MCP, REST, and CLI.
      15 npm
      13
      Apache 2.0
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables agents to work with an embedded graph database over MCP by exposing tools for entity storage, declarative rule creation, similarity search, association explanations, role-filtered queries, and historical edge inspection. It supports building and querying self-maintaining graphs locally with explainable derived relationships.
      5
      -
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to persist and retrieve structured memory across sessions and models via MCP tools for cataloging, searching, and saving facts, with automatic supersession and scope filtering.
      MIT

    TDQS

    B3/5.0

    Scored across 5 tools

    Disambiguation3/5

    The core split (context = current facts, history = facts over time, search = find subjects, annotate = write, related = neighbours) is mostly clear, but the boundaries blur: `search` with related_to/via and `context` with depth=1 both do what `related` does, and `context` vs `history` differ only by temporal framing. The descriptions do enough to steer an agent, but these are real overlaps rather than clean separations.

    Naming Consistency3/5

    All names are single lowercase tokens, which is tidy, but the grammatical convention is mixed: `search` and `annotate` are verbs while `context`, `history`, and `related` are nouns/adjectives. `context` in particular is a vague name for a read operation, so the set is readable but not predictable from a pattern.

    Tool Count5/5

    Five tools is well within the healthy range and each maps to a distinct capability of a temporal fact store: point-in-time read, timeline read, discovery, neighbourhood traversal, and write. Nothing feels padded or missing at the count level.

    Completeness3/5

    Read coverage is strong (current, historical, search, relations) and `annotate` covers ingestion, but there is no way to retract, correct, or supersede a fact, and no tool for managing the rules that `context` and `search` evaluate against. Agents hitting bad data or needing rule definitions will dead-end.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues