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PoisonDash MCP Server

by MoeAllami
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    Deploy Server
    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

    A4/5.0

    Scored across 24 tools

    Disambiguation5/5

    The tools are highly distinct, adhering strictly to resource-action separation (e.g., list_datasets vs get_dataset, start_generation vs get_generation_status). Even within workflows, the specialized nature of the PoisonDash operations ensures minimal confusion.

    Naming Consistency5/5

    Naming is extremely consistent, utilizing a predictable `action_resource` pattern across all operations. The use of standard verbs like `get`, `list`, `create`, `update`, `start`, and `cancel` maintains high predictability.

    Tool Count4/5

    With 24 tools, the set is on the heavier side, but this count is justifiable given the significant complexity of the underlying ML domain. Each tool provides a necessary and distinct piece of functionality for the end-to-end data poisoning workflow.

    Completeness5/5

    The tool surface is remarkably complete, covering the full lifecycle: data generation, configuration management, experiment initiation, execution tracking (logs/status), result analysis, and data retrieval. There are no obvious dead ends in the core workflow.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources