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MCP Agents

@CodeWithHarshAI

代码仓库

基本信息

分类

浏览器自动化

许可证

MIT license

传输方式

stdio

作者

CodeWithHarshAI

关于 MCP Agents

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 simpl

#automation#browser#mcp#openai#streamlit#mcp-server#mcp-client

MCP Agents 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "MCP-Agents": {
      "command": "node",
      "args": [
        "--version",
        "&&",
        "npm",
        "--version"
      ]
    }
  }
}

MCP Agents 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is MCP Agents?

MCP Agents is an AI-powered interactive browser assistant built with Streamlit, OpenAI, and Puppeteer using the Model Context Protocol (MCP). It allows users to type natural language commands to navigate, click, scroll, and extract content from websites hands‑free.

How to use MCP Agents?

Install Python 3.8+, Node.js + npm, and an OpenAI API key. Clone the repository, install Python dependencies, optionally start the Puppeteer agent with npx -y @modelcontextprotocol/server-puppeteer, then run streamlit run main.py. Create a mcp_agent.secrets.yaml file with your OpenAI API key to keep credentials secure.

Key features of MCP Agents

  • Interact with websites using simple English commands.
  • Visual automation with screenshots, clicks, and scrolling.
  • Flexible agent system powered by the modular MCP framework.
  • Secure API key storage with optional secrets config.
  • Fully interactive UI showing command results.

Use cases of MCP Agents

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

常见问题

1

What are the requirements to run MCP Agents?

Python 3.8 or newer, Node.js with npm, and an OpenAI API key.

2

How do I set up secrets?

Create a file named `mcp_agent.secrets.yaml` with your OpenAI API key and ensure this file is listed in `.gitignore`.

3

What kind of commands can I give?

Examples include "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", and "Scroll down and extract all h2 titles".

4

How do I start the application?

After installing dependencies and optionally starting the Puppeteer agent, run `streamlit run main.py` and visit `http://localhost:8501` in your browser.

5

What license is MCP Agents under?

MCP Agents is licensed under the MIT License.

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