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Related Servers

Alternatives to Learn Shell

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    Related Servers

    • A
      license
      B
      quality
      A
      maintenance
      Enables AI agents to act as a state-driven tutoring engine over MCP, with server-side mastery estimation, prerequisite checks, evidence-based assessment, and FSRS spaced review scheduling.
      58
      1
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables AI agents to share, search, and learn from structured lessons, ask and answer questions asynchronously, and contribute to a shared knowledge commons via MCP.
      19
      4 npm
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to create and manage personalized 30-day study courses, including web research with source validation, daily lessons, quizzes, and progress tracking through 12 MCP tools.
      1
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to generate teaching materials such as PPTs, handouts, lecture scripts, mind maps, teaching video storyboards, and Manim math animations, plus run quality checks and language normalization through 15 MCP tools.
      MIT

    TDQS

    A3.6/5.0

    Scored across 50 tools

    Disambiguation5/5

    Each tool targets a distinct resource/action combination, even within dense families like add/update/record. Closely related tools such as add_lesson_patch and update_lesson have clearly defined boundaries based on lesson progress state. The overlap risk is minimal despite the large surface.

    Naming Consistency3/5

    Most tools follow a verb_noun pattern (add_lesson, create_course, get_context), but the live_* and adhoc_* families invert this to noun_verb (live_message_send, adhoc_thread_get) or use ambiguous nouns like live_pending. This creates a noticeable inconsistency, though each family is internally consistent.

    Tool Count1/5

    At exactly 50 tools, the server is at the extreme end of the scale and falls into the '50+ tools' criterion. Even for a complex tutoring platform, the surface is unwieldy and likely to increase selection latency and cognitive load for agents. A more curated set of 20-30 tools would be far more appropriate.

    Completeness4/5

    The toolset covers the full lifecycle: pair creation, contract negotiation, course/lesson authoring, exercise grading, live session management, feedback loops, and reflection. Minor gaps exist (e.g., no update/delete for courses, no direct list-all lessons), but overview tools like get_context and get_teacher_inbox make these workable.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues