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ai-collab-mcp

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    TDQS

    A4.2/5.0

    Scored across 6 tools

    Disambiguation5/5

    The tools split clearly into discovery (list_providers, list_agents, list_models) and execution (run_pipeline, run_orchestrator, run_debate). Each tool targets a distinct resource or workflow style, so an agent is unlikely to select the wrong one.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern: list_* for discovery operations and run_* for execution modes. This makes the tool surface predictable and easy to navigate.

    Tool Count5/5

    Six tools is a well-scoped size for an AI collaboration server. The three list tools support the three run tools without unnecessary duplication or overwhelming sprawl.

    Completeness5/5

    The surface covers the full workflow: discovering available providers, agents, and model capabilities, then executing collaboration via pipeline, orchestrator, or debate. Configuration management appears intentionally out of scope rather than a missing capability.

    Maintenance

    ActivityActive
    ResponsivenessNo issues

    Resources