trackmcp
Back to directory
CodeWithHarshAI

mcp-agents

View on GitHub

MCP Agents is an AI-powered browser automation tool that lets you interact with websites using natural language. Built with Streamlit, OpenAI, and Puppeteer via the Model Context Protocol (MCP), it supports multi-step navigation, interaction, and content extraction—all with simple text commands.

2 stars PythonAI & Machine Learning Updated Jul 26, 2025
automationbrowsermcpmcp-clientmcp-serveropenaistreamlit

Documentation

🌐 MCP Agents

MCP Agents is an AI-powered interactive browser assistant built with Streamlit, OpenAI, and Puppeteer using the Model Context Protocol (MCP). Type natural language commands like *"Go to Wikipedia and search for Mars"* and the app will navigate, click, scroll, and even extract content — all hands-free.


🚀 Features

  • Talk to the Web — Interact with websites using simple English commands
  • Visual Automation — Take screenshots, click elements, and scroll pages effortlessly
  • Flexible Agent System — Powered by the modular MCP Agent framework
  • Secure Integration — API keys stored safely with optional secrets config
  • Fully Interactive UI — See command results directly in the app interface

🎯 Use Cases

  • 💼 Product scraping, news summarization, automated browsing workflows
  • 🧪 Educational bots that walk through websites
  • 📰 Daily content extraction from dynamic pages

⚙️ Requirements

  • Python 3.8 or newer
  • Node.js + npm (for Puppeteer server)
  • OpenAI API key

⚡ Quick Start

bash
# Clone and enter the project
$ git clone https://github.com/your-username/mcp-agents.git
$ cd mcp-agents

# Install Python dependencies
$ pip install -r requirements.txt

# Verify Node.js setup
$ node --version && npm --version

# Optional: Start Puppeteer agent
$ npx -y @modelcontextprotocol/server-puppeteer

# Run the app
$ streamlit run main.py

Visit http://localhost:8501 in your browser.


🔐 Configure Secrets

Create a file named `mcp_agent.secrets.yaml`:

yaml
openai:
  api_key: "your-openai-api-key"

➡️ Make sure this file is listed in `.gitignore` to avoid leaking credentials.


💬 Example Commands You Can Try

  • "Go to www.wikipedia.org"
  • "Search for black holes and summarize the page"
  • "Click on the first heading"
  • "Take a screenshot of the hero section"
  • "Scroll down and extract all h2 titles"

📁 Project Overview

code
mcp-agents/
├── main.py                     # Streamlit application
├── requirements.txt           # Python dependencies
├── README.md                  # This file
├── mcp_agent.config.yaml      # Config for Puppeteer + agent setup
├── mcp_agent.secrets.yaml     # API secrets (ignored from Git)
├── .gitignore                 # File exclusions

📄 License

Licensed under the MIT License.


🙋‍♂️ Created By

Built with ❤️ by Harsh.

Powered by the open agent framework from MCP and inspired by LastMileAI tooling.


👨‍💻 Want to build your own AI-powered automation agent? Fork this repo and start customizing!

Frequently asked questions

What is mcp-agents?

mcp-agents is MCP Agents is an AI-powered browser automation tool that lets you interact with websites using natural language. Built with Streamlit, OpenAI, and Puppeteer via the Model Context Protocol (MCP), it supports multi-step navigation, interaction, and content extraction—all with simple text commands.

How do I install mcp-agents?

Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

Is mcp-agents open source?

Yes — it is hosted on GitHub at https://github.com/CodeWithHarshAI/MCP-Agents and has 2 stars.

Related MCP tools

Run your own MCP server? See who uses it and what to fix.

Measure it with TrackMCP