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LamantinAI

kaeru memory

by LamantinAI
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Rust
Hybrid

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    • nMEMORY

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      AGPL 3.0
    Deploy Server
    Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

    TDQS

    C2.7/5.0

    Scored across 35 tools

    Disambiguation3/5

    Many tools target related memory operations, and several boundaries are fuzzy: claim vs verdict both can save verdict evidence, note/reference/synthesise all create records, and context/read/search overlap in retrieval. Detailed descriptions mitigate much of the confusion, but an agent still has to reason carefully to choose the right tool.

    Naming Consistency3/5

    All names are snake_case, but conventions are mixed: some are single verbs or nouns (task, claim, note, read), some are verb_noun (task_update, link_cloud), and others are noun_verb or noun_noun (initiative_manage, cloud_recall, board_config). The set is readable but does not follow a predictable pattern.

    Tool Count2/5

    With 35 tools, the surface is heavy for a memory/knowledge server and includes many niche maintenance, sharing, and cloud-sync operations. While the domain is broad, the count exceeds a well-scoped set and likely burdens tool selection.

    Completeness4/5

    The surface covers an extensive memory lifecycle: creation, revision, replacement, relations, review, trails, lifecycle tiers, retention, audit history, search/read/context, initiatives, export, and cloud sharing. Minor gaps remain, such as no import counterpart to export and no obvious initiative creation action beyond management.

    Maintenance

    ActivityActive
    ResponsivenessWithin a week

    Resources