AI导哈

AI助手

基于LangChain、Groq和FastAPI构建的AI助手，提供对话AI、浏览器自动化、天气数据和学术论文搜索等功能。

  • by maryemchk
  • Python
  • 本地部署
  • 更新于
在 GitHub 查看 maryemchk/ai-assistant-mcp

使用说明

AI Assistant with LangChain, Groq & MCP

This project is an AI Assistant built using LangChain, LangChain-Groq, and FastAPI, enhanced with MCP servers for additional functionality such as web automation, weather data, and academic paper search.

Features

  • Conversational AI using Groq Chat model
  • Exposed API endpoints via FastAPI
  • Asynchronous communication using aiohttp and WebSockets
  • Environment-based configuration via python-dotenv
  • Integration with MCP servers: browser automation, weather API, and Semantic Scholar API

Tools & Technologies

AI & LLM Frameworks

  • LangChain → Orchestrates language models, chains, and memory
  • LangChain-Groq → Provides Groq Chat model integration

Web & API Frameworks

  • FastAPI → Serves the AI Assistant as HTTP endpoints
  • Uvicorn → ASGI server to run FastAPI apps
  • aiohttp & websockets → For asynchronous HTTP requests and real-time communication

Environment & Dependency Management

  • python-dotenv → Loads API keys and environment variables from .env
  • venv → Isolated Python virtual environment for dependencies

MCP (Modular Chat Platform) Tools

  • mcp-use → Manages and runs multiple MCP agents locally or remotely
  • MCP Servers in this project:
    • Playwright MCP Server → Browser automation and web scraping
    • MCP Weather Server → Fetches weather information dynamically
    • MCP Semantic Scholar Server → Academic paper metadata and search

Note: API keys are stored in .env and should never be pushed to GitHub. Use .env.example with placeholders for sharing.

Project Structure

AIAssistantWithMCP/
│ app.py # FastAPI entrypoint
│ requirements.txt # Python dependencies
│ .env # Environment variables (API keys)
│ venv/ # Virtual environment
│ README.md
│
├── mcp_servers/ # MCP server configurations
└── modules/ # Custom Python modules (if any)

Installation

# 1. Clone the repo
git clone https://github.com/maryemchk/ai-assistant-mcp.git
cd ai-assistant-mcp

# 2. Create a virtual environment
python -m venv venv
.\venv\Scripts\Activate.ps1  # Windows PowerShell
# OR
source venv/bin/activate      # Mac/Linux

# 3. Install dependencies
pip install -r requirements.txt

# 4. Create .env file from template
copy .env.example .env
# Fill in your API keys

License

MIT License

Acknowledgements

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