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Interview Prep MCP Server

by bemnetbeshah
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Python
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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

    A3.7/5.0

    Scored across 15 tools

    Disambiguation5/5

    Each tool targets a distinct resource or action: study hierarchy reads/creates/deletes, attempt logging, due queue, history, and data privacy. list_subtopics and get_due_subtopics are clearly different because one returns all subtopics while the other returns the spaced-repetition queue.

    Naming Consistency5/5

    Tool names follow a consistent verb_noun pattern with hierarchical nouns: list_*, create_*, delete_*, and get_*. Pluralization is predictable, and no mixed casing or vague verbs are present.

    Tool Count5/5

    15 tools is at the upper bound of the ideal range, but each tool earns its place by covering study hierarchy management, spaced-repetition workflow, history inspection, and user data controls. The scope matches the server's stated purpose without unnecessary redundancy.

    Completeness3/5

    The core hierarchy and spaced-repetition workflow are well covered, but update_study and update_topic are missing while update_subtopic exists. This creates an incomplete CRUD surface for higher-level resources; agents cannot rename or edit a study or topic without deleting and recreating it.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources