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Alternatives to EMET

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    Related Servers

    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables agents to read and write a durable, append-only memory with verified provenance, supporting search, record capture, and context preparation across sessions and machines.
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to maintain persistent memory across sessions with verifiable source receipts, supporting explicit remember, recall, inspect, correct, and forget operations.
      6 npm
      20
      Apache 2.0
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables AI agents to store and recall an append-only, hash-chained memory with citation-backed semantic search, fact verification, contradiction detection, and replay/audit capabilities through local MCP tools.
      1
      AGPL 3.0
    • -
      license
      Not graded
      quality
      Not graded
      maintenance
      Enables self-hosted, persistent AI identity and long-term memory across clients, models, and agent surfaces, with multi-resident isolation, shared world knowledge, governed memory writes, correction and forgetting, keyword or optional semantic recall, and MCP or HTTP access.
      -
    • A
      license
      Not graded
      quality
      C
      maintenance
      Enables autonomous multi-agent workflows to capture, preserve, and retrieve immutable transcripts and atomic memory cards through a local MCP server, providing tools for forensic search, topic mapping, and structured fact access without losing context fidelity.
      1
      MIT

    TDQS

    A3.6/5.0

    Scored across 29 tools

    Disambiguation4/5

    Tools target distinct resources and actions, and descriptions explicitly differentiate overlapping clusters such as recall vs semantic_recall vs query_layer, and emet_transcript_append vs save_transcript. However, multiple retrieval and transcript tools still share similar purposes, so an agent must read carefully to avoid misselection.

    Naming Consistency3/5

    All names use snake_case, but the set mixes prefixed tools (emet_status, emet_session_open) with bare tools (query_layer, write_doc) and mixes verb_noun with noun_verb patterns (corpus_recall, semantic_recall). It remains readable, but the convention is not consistent.

    Tool Count2/5

    At 29 tools, the surface is heavy and exceeds the typical 3–15 range. While the domain is broad, several specialized tools (emet_floor, emet_status, emet_setup_complete, access creation) could likely be consolidated or parameterized.

    Completeness4/5

    The set covers memory layers, transcripts, versioned documents, setup, diagnostics, and access creation comprehensively. Minor gaps remain: no access revocation/list, no explicit memory deletion or redaction tool, and no corpus population tool.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues