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Advanced MCP Agent Streamlit App

@Rizwankaka

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

Rizwankaka

关于 Advanced MCP Agent Streamlit App

using different mcp servers to automate the tasks

#mcp-agent#streamlit#automation

Advanced MCP Agent Streamlit App 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-brower-use": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "-e",
        "."
      ]
    }
  }
}

Advanced MCP Agent Streamlit App 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 Advanced MCP Agent Streamlit App?

A modern Streamlit application that demonstrates the capabilities of the MCPAgent with built-in conversation memory. It provides an interactive chat interface, web browsing and search capabilities, and model selection from available models. Designed for developers and users exploring AI agent interactions.

How to use Advanced MCP Agent Streamlit App?

Install dependencies with pip install -e . or uv pip install -e ., set the GROQ_API_KEY environment variable in a .env file, then run streamlit run app.py. The app uses browser_mcp.json for configuration. Use the "New Conversation" button to reset the session.

Key features of Advanced MCP Agent Streamlit App

  • 🤖 Interactive chat interface with the MCPAgent
  • 🧠 Built-in conversation memory for contextual interactions
  • 🌐 Web browsing and search capabilities
  • 🔄 Model selection from available models
  • 📱 Responsive design with modern UI

Use cases of Advanced MCP Agent Streamlit App

  • Conduct interactive conversations with an AI agent that maintains context
  • Perform web browsing and search tasks through the agent
  • Test and compare different models using the model selection feature
  • Explore the MCPAgent’s capabilities in a demo environment
  • Experiment with conversation memory in a session-based app

常见问题

1

What is required to run the app?

Python 3.11 or newer, dependencies installed, and a `GROQ_API_KEY` set in a `.env` file.

2

How do I install dependencies?

Run `pip install -e .` or `uv pip install -e .` from the project directory.

3

How do I start the app?

Run `streamlit run app.py` in the terminal.

4

How does conversation memory work?

The app uses Streamlit’s session state to maintain conversation history during the session. You can start a new conversation with the "New Conversation" button.

5

What configuration file is used?

The app uses `browser_mcp.json` for configuration, allowing modification of available models and other settings.

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