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Animuni-Express

SubMCP

by Animuni-Express
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Python
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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

    A5/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a clearly distinct role: delegate runs one sub-agent, delegate_parallel runs multiple independent ones concurrently, and list_agents inspects capabilities. The descriptions explicitly delineate when to use each, with delegate_parallel contrasted against delegate for independent vs. sequential work, leaving no ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent snake_case verb-based pattern: delegate, delegate_parallel, list_agents. The shared 'delegate' prefix in the first two creates an obvious family, and list_agents follows a verb_noun structure, making the naming predictable and readable.

    Tool Count5/5

    Three tools is a well-scoped count for a sub-agent delegation server. Each tool covers a necessary function—single execution, parallel execution, and environment introspection—without redundancy or missing core operations.

    Completeness5/5

    The tool surface fully covers the delegation workflow: run one task, run several tasks concurrently, and check the server's current capabilities and limits. No obvious gaps exist; the delegate and delegate_parallel return final reports directly, making the workflow self-contained.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

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