Advanced MCP Agent Streamlit App
About
using different mcp servers to automate the tasks
Explore
- 🤖 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
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Advanced MCP Agent Streamlit AppCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
The app uses the browser_mcp.json file for configuration. You can modify the available models and other settings in this file.
1. Make sure you have Python 3.11 or newer installed
2. Install dependencies:
``bash`
pip install -e .
Or using uv:
bash`
uv pip install -e .
3. Set up your environment variables in file:`
GROQ_API_KEY=your_api_key_here
bash
To run the Streamlit app:
streamlit run app.py
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"advanced mcp agent streamlit app": {
"mcp-brower-use": {
"command": "uv",
"args": [
"pip",
"install",
"-e",
"."
]
}
}
}
}McpServers
{
"mcp-brower-use": {
"command": "uv",
"args": [
"pip",
"install",
"-e",
"."
]
}
}Features
- 🤖 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 UISetup and Installation
1. Make sure you have Python 3.11 or newer installed 2. Install dependencies: ``bash
pip install -e .
`
Or using uv:
`bash
uv pip install -e .
`
3. Set up your environment variables in .env file:
`
GROQ_API_KEY=your_api_key_here
`
Running the App
To run the Streamlit app:
`bash
streamlit run app.py
`
Configuration
The app uses the browser_mcp.json` file for configuration. You can modify the available models and other settings in this file.
Notes
- The app uses Streamlit's session state to maintain the conversation history during the session - The agent is initialized when the app starts, which may take a few seconds - You can start a new conversation at any time using the "New Conversation" button in the sidebarSign in to leave a review
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