About Advanced MCP Agent Streamlit App
A Streamlit chat app for people using MCPAgent to automate tasks with different MCP servers. It includes conversation memory, web browsing, and model selection.
Key features
- 01Interactive chat interface
- 02Conversation memory
- 03Web browsing and search
- 04Model selection
- 05Responsive interface
Use cases
- 01Automate tasks through chat
- 02Search the web during conversations
MCP support
The app uses MCPAgent with configured MCP servers to support chat interactions and task 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 READMEAdvanced MCP Agent Streamlit App
A modern Streamlit application demonstrating the capabilities of the MCPAgent with built-in conversation memory.
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 UI
Setup and Installation
- Make sure you have Python 3.11 or newer installed
- Install dependencies:
pip install -e .
Or using uv:
uv pip install -e .
- Set up your environment variables in
.envfile:
GROQ_API_KEY=your_api_key_here
Running the App
To run the Streamlit app:
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 sidebar
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.