KLH Campus Assistant

KLH Campus Assistant

An MCP server for KLH University Hyderabad that provides tools for CGPA calculation, schedule conflict checking, study group and course search, club and exam info, library lookup, and resources for campus FAQ and curriculum requirements.

Category
访问服务器

README

KLH Campus Assistant — MCP Demo

A Model Context Protocol (MCP) server for KLH University Hyderabad, built with FastMCP. It exposes 7 tools (CGPA calculator, schedule-conflict checker, study-group finder, course search, club finder, exam schedule, library lookup) and 2 resources (campus FAQ, curriculum requirements) over local stdio — no deployment, no network service, just Python.

Files

  • server.py — the MCP server. Run directly with python server.py (it will idle waiting for a client — that's expected).
  • client.py — a terminal demo that connects to the server and drives a scripted conversation through Claude.
  • web/app.py + web/index.html — a small FastAPI + browser chat UI for a live, on-screen demo.
  • requirements.txt — all dependencies for server, CLI client, and web demo.

Setup & Running the Demo

Requirements

  • Python 3.10+ (project written for Python 3.14)
  • An Anthropic API key (get one at https://console.anthropic.com/keys)

Step 1: Install Dependencies

Open a terminal in this folder and run:

pip install -r requirements.txt

Step 2: Set Your API Key

You need to set your Anthropic API key as an environment variable:

On macOS/Linux:

export ANTHROPIC_API_KEY=sk-ant-...

(Replace sk-ant-... with your actual API key)

On Windows (Command Prompt):

set ANTHROPIC_API_KEY=sk-ant-...

On Windows (PowerShell):

$env:ANTHROPIC_API_KEY="sk-ant-..."

Step 3: Run the Terminal Demo (Fastest)

Run this command to see the MCP server in action with a scripted demo:

python client.py

This will automatically start the MCP server and walk through several examples:

  • CGPA calculation
  • Schedule conflict checking
  • Study group search
  • Club search

Step 4: Run the Interactive Web Chat (Recommended)

For a live, interactive demo with a visual UI:

# Navigate to the web folder
cd web

# Start the app (on Windows, use 'python -m uvicorn' instead)
uvicorn app:app --reload --port 8000

Then open your browser and go to http://localhost:8000

  • Paste your API key into the page
  • Chat with the assistant — every tool call appears as an expandable card
  • Try queries like:
    • "What's my CGPA?"
    • "Do I have any schedule conflicts?"
    • "Find study groups for Data Structures"
    • "List all clubs at KLH"

Troubleshooting

  • ModuleNotFoundError: Make sure you installed dependencies with pip install -r requirements.txt
  • API key errors: Verify your API key is set correctly (it should start with sk-ant-)
  • Port 8000 already in use: Try a different port: uvicorn app:app --reload --port 8001

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选