Advanced MCP Agent Streamlit App

@Rizwankaka

Repository

Basic information

About Advanced MCP Agent Streamlit App

using different mcp servers to automate the tasks

#mcp-agent #streamlit #automation

Advanced MCP Agent Streamlit App config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "mcp-brower-use": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "-e",
        "."
      ]
    }
  }
}

Advanced MCP Agent Streamlit App tools

Tool list not available yet

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We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

Frequently asked questions

What is required to run the app?

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

How do I install dependencies?

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

How do I start the app?

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

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.

What configuration file is used?

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

Comments

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