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Maheshdayyala

CampusMind-AI

by Maheshdayyala
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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 22 tools

    Disambiguation4/5

    Most tools target distinct resources and actions, but some overlap exists between get_review_due and suggest_review_plan (both about review scheduling) and between ask_question and explain_concept (both about learning support). Descriptions help clarify boundaries, but an agent might occasionally pick the wrong tool without careful reading.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case, with verbs like get, list, log, set, start, and end. The naming is uniform and predictable, making it easy to infer functionality from the name.

    Tool Count3/5

    With 22 tools, the server is on the heavier side of the typical range. While each tool serves a purpose in the learning assistant domain, some consolidation could reduce redundancy (e.g., merging or streamlining review-related tools), making the count feel slightly bloated.

    Completeness4/5

    The tool set covers the core learning workflow well: authentication, course viewing, concept mastery, questioning, explanations, quiz logging, study sessions, review scheduling, goals, and voice interaction. Minor gaps exist, such as no way to list or update study goals and no direct way to view all logged topics beyond search, but these are workable.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources