About 🌐 MCP Agents
MCP Agents is a Streamlit browser automation app for people who want to control websites with natural-language commands. It uses OpenAI and Puppeteer to navigate pages, interact with elements, take screenshots, and extract content.
Key features
- 01Natural-language website commands
- 02Page navigation, clicking, and scrolling
- 03Screenshots and content extraction
- 04Interactive results in the app
- 05Optional secrets configuration
Use cases
- 01Scrape product information from websites
- 02Summarize news and extract page content
- 03Guide learners through website interactions
MCP support
The project uses the Model Context Protocol with a modular MCP Agent framework and a Puppeteer server for browser automation.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project README🌐 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
# 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:
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
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!
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.