Building Agents with Amazon Nova Act and MCP

This repository demonstrates how to build intelligent web automation agents using Amazon Nova Act integrated with MCP (Model Context Protocol). MCP provides a standardized way to connect AI models to different data sources and tools - think of it like a "USB-C port for AI applications."

Overview

This project showcases the integration between:

• Amazon Nova Act: A powerful web automation tool for creating agents that interact with web pages
• MCP (Model Context Protocol): An open protocol that standardizes how applications provide context to LLMs
• Amazon Bedrock: Managed service that provides foundation models through a unified API

Architecture

The project follows MCP's client-server architecture:

• MCP Host: Claude Desktop or other AI tools that want to access Nova Act capabilities
• MCP Client: Protocol clients maintaining 1:1 connections with the Nova Act server
• MCP Server: A Nova Act server exposing web automation capabilities through the standardized protocol
• Remote Services: Web services that Nova Act interacts with through browser automation

Key Features

• Standardized LLM integration through MCP
• Automated web navigation and interaction via Nova Act
• Parallel execution of multiple browser tasks
• Data extraction and processing
• Screenshot capture and visual verification
• Session management and browser control
• Seamless integration with Claude Desktop
• Access to foundation models via Amazon Bedrock

Prerequisites

• Operating System: MacOS or Ubuntu (Nova Act requirements)
• Python 3.10 or higher
• A valid Nova Act API key (obtain from https://nova.amazon.com/act)
• Node.js (for Claude Desktop integration)
• Amazon Bedrock access:
  • Amazon Bedrock enabled in your AWS account
  • Claude 3.5 Sonnet V2 model enabled (this is default for this example)
  • AWS credentials and region properly configured - AWS CLI Quickstart Guide

Project Structure

The repository contains two main example directories:

1. Streamlit Examples (streamlit_examples/)

• video_game_research_st.py: A comprehensive tool that:
  • Finds top games for any selected gaming system
  • Searches Amazon in parallel for pricing and details
  • Creates interactive result tables
  • Saves research data for future reference

2. MCP Examples (mcp_examples/)

• nova_act_mcp_server.py: MCP-compliant server implementation exposing Nova Act capabilities
• nova_act_mcp_client.py: Example MCP client implementation
• Demonstrates integration with Claude Desktop and other MCP hosts

3. Nova Act Examples (nova_act_examples/)

• get_coffee_maker.py: Simple example demonstrating how to:
  • Initialize Nova Act with a starting web page
  • Perform basic web search and selection actions
  • Extract information from product pages
• multi_monitor.py: Advanced example showing:
  • Parallel execution of web tasks using ThreadPoolExecutor
  • Searching and comparing multiple products simultaneously
  • Structured data extraction and comparison
  • Error handling for robust web automation

Getting Started

1. Clone this repository

2. Install dependencies:

   pip install -r requirements.txt
   

3. Set your Nova Act API key:

   export NOVA_ACT_API_KEY="your_api_key"
   

4. Make sure your environment has AWS configured correctly - https://docs.aws.amazon.com/cli/latest/userguide/getting-started-quickstart.html

Usage

Running Streamlit Examples

cd streamlit_examples
streamlit run video_game_research_st.py

Running the MCP Server and Client

cd mcp_examples
python nova_act_mcp_client.py nova_act_mcp_server.py

The command above will:

1. Start the MCP server that exposes Nova Act

... View full README on GitHub