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MCP verified MIT-0 Self-run

Sample Agents With Nova Act And Mcp

mcp-aws-samples-sample-agents-with-nova-act-and-mcp · by aws-samples

Discover how to build agents that can perform actions on websites by combining Amazon Nova Act with Model Context Protocol (MCP).

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Install

$ agentstack add mcp-aws-samples-sample-agents-with-nova-act-and-mcp

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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Declared compatibility

Claude CodeClaude DesktopCursorWindsurf

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

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
  1. Install dependencies:

``bash pip install -r requirements.txt ``

  1. Set your Nova Act API key:

``bash export NOVA_ACT_API_KEY="your_api_key" ``

  1. 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 capabilities
  2. Launch the MCP client that connects to the server
  3. Enable communication between Claude and the Nova Act browser automation

Claude Desktop Integration

For setting up and using this server with Claude Desktop, please follow the official Claude Desktop MCP Setup Guide. The guide covers:

  • Installing and configuring Claude Desktop
  • Setting up MCP servers in Claude Desktop
  • Troubleshooting common issues
  • Example usage and best practices

Best Practices

  1. Follow MCP's standardized approach for exposing capabilities
  2. Always close browser sessions when done
  3. Use headless mode for automated tasks not requiring visual feedback
  4. Break down complex actions into smaller, specific instructions
  5. Use schemas when expecting structured data responses
  6. Save important results to files for persistence
  7. Handle errors appropriately in your code

Security

See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.

License

This library is licensed under the MIT-0 License. See the LICENSE file.

Additional Resources

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.