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  • F
    license
    Not graded
    quality
    A
    maintenance
    Enables MCP-compatible coding tools to share a portable, local-first AI work identity and memory layer, so preferences, decisions, lessons, and project context persist across sessions and clients. Users can inspect, edit, approve, and override what the AI receives, keeping the store on their own machine without a cloud account.
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  • F
    license
    Not graded
    quality
    A
    maintenance
    Provides a local-first, user-owned identity layer that lets MCP-compatible coding agents start from the same approved preferences, quality bar, lessons, and project context. Memory stays in inspectable local files that can be reviewed, edited, overridden, and carried across different AI coding tools.
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  • A
    license
    Not graded
    quality
    B
    maintenance
    Provides a local-first persistent memory layer for coding assistants, enabling cross-project user preferences, per-project durable and working memory, session archives, and reflective recommendations through MCP tools.
    43 npm
    MIT
  • F
    license
    Not graded
    quality
    A
    maintenance
    Enables a local-first, user-owned AI work identity layer that lets multiple MCP coding tools share approved preferences, quality standards, lessons, decisions, and project context, with local files you can inspect, edit, and override.
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  • A
    license
    Not graded
    quality
    C
    maintenance
    Provides long-term local memory for AI coding agents via MCP, enabling persistent recall of preferences and project facts across chat sessions.
    1
    MIT
  • F
    license
    Not graded
    quality
    A
    maintenance
    Enables MCP-compatible coding agents to start from one portable, local-first identity and long-term knowledge layer, so preferences, quality bars, lessons, decisions, and project context carry across tools instead of being relearned per session. Everything the AI writes stays in local files the user can inspect, edit, approve, or override.
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TDQS

A3.8/5.0

Scored across 19 tools

Disambiguation2/5

Four retrieval tools (get_user_context, get_identity_card, get_resume_brief, get_recall) all return overlapping user-context/knowledge bundles with subtle lifecycle distinctions that an agent could easily confuse, especially at session start. memory_store also overlaps with the three add_* tools. The descriptions cross-reference each other well, but the boundary between 'startup context', 'resume brief', and 'recall surface' remains genuinely fuzzy.

Naming Consistency4/5

The set follows a clean verb_noun snake_case pattern: ten get_* readers, three add_* knowledge writers, plus search_, update_, and save_ verbs. Minor deviations exist — memory_store inverts the order, doctor is a bare noun, and wrap_up_session uses a phrasal verb — but the overall convention is highly predictable.

Tool Count3/5

19 tools sits at the heavy end of the range for a memory server, and the context-retrieval cluster (get_user_context, get_resume_brief, get_recall) shows clear consolidation opportunity. Most tools do serve a legitimate lifecycle function, so it is borderline rather than bloated.

Completeness3/5

Create/read coverage is strong for lessons, decisions, playbooks, identity, and project snapshots, with session lifecycle well handled. However, there is no update or delete surface for knowledge items, making get_knowledge_history a read-only dead end, and extract_session_insights is repeatedly referenced in descriptions but absent from the tool set — a real gap that will cause agent confusion.

Maintenance

ActivityActive
ResponsivenessResponsive