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timeline-mcp

by bmit20
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Python
Remote

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    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    B3.3/5.0

    Scored across 5 tools

    Disambiguation4/5

    Most tools are clearly separated by their role in the pipeline: extraction, state building, summarization, and querying. There is minor overlap between build_timeline_state and upsert_message_into_timeline since both aggregate events and recompute derived fields, but the incremental vs bulk distinction is clear enough.

    Naming Consistency4/5

    The naming mostly follows a verb_noun pattern: extract_timeline_events, build_timeline_state, summarize_timeline_context, upsert_message_into_timeline. The exception is days_since_event, which is not a verb-led action name and breaks the pattern slightly.

    Tool Count5/5

    Five tools is well-scoped for a focused timeline-management server. Each tool covers a distinct stage of the workflow without redundancy or excessive granularity.

    Completeness4/5

    The core lifecycle is covered: extraction, state construction, incremental updates, summarization, and queries. Minor gaps include lack of an explicit reset/clear operation or a way to remove individual events, but these are not critical for the intended use case.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources