MCPMarket
出售技能Power Your Agents连接
  1. 首页
  2. 服务器
  3. ExamAI

ExamAI

AdesharaBrijeshbyAdesharaBrijesh
•
数据科学与机器学习
生产力与工作流
学习与文档

Automates the generation, conduction, and evaluation of exams through an AI-powered assessment platform leveraging RAG and multi-LLM validation.

Related MCPs

View more
  • datawiz168

    Snowflake Integration

    Enables Claude to execute SQL queries and interact with Snowflake databases.

  • tinybirdco

    Tinybird

    Connects to a Tinybird Workspace and interacts with data sources and API endpoints using the Model Context Protocol.

  • ThetaBird

    Axiom

    Enables AI agents to query data stored in Axiom using the Axiom Processing Language (APL).

Related Skills

View all
  • openclaw

    Diagram Maker & Visualizer

    Generates professional SVG, HTML, and Excalidraw diagrams for software architecture, system flows, and educational concepts.

  • openclaw

    GH Issues Auto-Fixer

    Automates the end-to-end GitHub issue lifecycle by spawning sub-agents to implement code fixes, open pull requests, and resolve review comments.

  • openclaw

    Discord Integration

    Manages Discord operations including messaging, reactions, and channel management directly through Claude.

MCPMarket

发现可将 Claude 和 Cursor 等 MCP 客户端连接到您喜爱工具的 MCP 服务器。浏览 MCP 市场开始使用。

浏览

  • MCP 搜索
  • MCP 服务器
  • MCP 客户端
  • Claude 技能
  • MCP Market Hub
  • 分类
  • 什么是 MCP 服务器?
  • Model Context Protocol

排行榜

  • 今日热门 MCP
  • 今日热门 Claude 技能
  • Claude 技能 Top 100
  • MCP 服务器 Top 100

关于

  • 新闻
  • 提交
  • 联系我们

© 2026 MCP 市场。保留所有权利。·Privacy·Terms

ExamAI is an AI-driven assessment platform designed to revolutionize the way exams are created, administered, and graded. It harnesses modern GenAI architectures, including Retrieval-Augmented Generation (RAG) over course content and multi-LLM validation, to generate new exams from course materials or evaluate existing question papers. The platform prioritizes performance, explainability, and real-world workflows, offering features like deterministic blueprint-based structures, offline-safe exam conduction via React and IndexedDB, and explainable semantic grading for descriptive answers with evidence tracing.

主要功能

01Retrieval-Augmented Generation (RAG) for exam content creation
02Offline-safe answer storage via IndexedDB for resilient exam conduction
030 GitHub stars
04Multi-LLM generation and verification for robust questions and answers
05Semantic grading and explainable scores for descriptive answers
06Deterministic blueprint-based exam structure generation

使用案例

01Conducting automated MCQ exams or section-wise descriptive exams with offline capabilities.
02Evaluating existing question papers by generating reference answers and rubrics.
03Generating new exams from course materials and topics.