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Alternatives to EMET

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    • 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.
      2 npm
      31
      Apache 2.0
    • A
      license
      A
      quality
      A
      maintenance
      Enables multiple AI agents on one machine to write, search, fetch, link, and give feedback on a shared local store of Markdown-backed facts, preferences, and conventions that persists across sessions. Memories gain confidence as different hosts confirm their use and can be distilled into denser ones, so agents stop re-discovering the same context.
      5
      507 PyPI
      1
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to commit and read shared memory facts that must cite a registered artifact SHA-256 receipt, with confidence that decays over time and a cascade rollback that quarantines a poisoned fact plus every downstream decision derived from it. Exposes provenance tracing (blame), evidence registration, and commit/revert tools over stdio so multi-agent teams can detect and unwind cascading memory poisoning.
      1
      MIT
    • 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

    TDQS

    B3.4/5.0

    Scored across 38 tools

    Disambiguation3/5

    There are several overlapping clusters: recall/semantic_recall/query_layer/corpus_recall all retrieve memories, and save_transcript/emet_transcript_append/revise_transcript plus write_doc/patch_doc/write_doc_begin-append-commit create multiple write paths. Descriptions explain the distinctions (keyword vs semantic vs structured, fallback vs primary, small edit vs full write), but an agent must read carefully to pick correctly.

    Naming Consistency2/5

    Most names are snake_case, but many carry an emet_ prefix while others do not (recall, write_doc, query_layer), and several prefixed names are bare nouns (emet_pages, emet_status, emet_floor, emet_gaps) rather than verb_noun. The result is a mixed convention that is readable but not predictable.

    Tool Count2/5

    38 tools is heavy for any single server and sits well above the 15-tool comfort zone. The domain is genuinely complex (memory layers, documents, transcripts, pages, access, audits), so many tools are justified, but the surface feels bloated and could likely be consolidated.

    Completeness4/5

    Coverage is broad: setup/identity, all memory-layer CRUD with supersession, versioned documents with staged writes, transcripts, page reads and linting, gap analysis, and guest/member access. Deletion is intentionally absent and documented, and minor gaps (e.g. no explicit bulk or merge tool) are workable.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues