About
The Nova Act MCP Server exposes Amazon Nova Act’s browser‑automation tools via the Model Context Protocol, enabling AI agents to start sessions, execute natural language instructions, capture screenshots, and manage browser state with minimal setup.
Capabilities
Nova Act MCP Server
The Nova Act MCP server bridges the gap between AI assistants and real‑world web interactions by exposing Amazon Nova Act’s browser automation capabilities through the Model Context Protocol. In practical terms, it lets an AI agent launch a headless browser, execute natural‑language instructions on that page, capture screenshots, and manage session lifecycles—all without the developer writing custom browser‑automation code. This capability is essential for developers building AI workflows that require dynamic web scraping, form submission, or visual validation.
At its core the server provides a small but powerful set of tools: to spin up a new browser instance, to let the assistant dictate actions in plain English, for visual feedback and state inspection, and session management tools such as and . These primitives are designed to be composable, enabling complex sequences like “open the login page, fill in credentials, submit, and capture a screenshot of the dashboard” to be expressed succinctly from within an MCP‑compatible client such as Claude Desktop or VS Code.
Key features include file‑based screenshots that bypass MCP’s message size limits, optimized image quality for efficient bandwidth usage, and robust error handling for flaky network conditions. The server also ships with an integrated MCP Inspector UI that lets developers debug tool calls in real time, and a suite of advanced tools—, , and —that extend the automation surface to file downloads, raw HTML inspection, and log archival.
In real‑world scenarios Nova Act MCP is invaluable for building AI agents that need to interact with e‑commerce sites, automate testing of web applications, or gather data from pages that rely heavily on JavaScript. By exposing browser control through MCP, developers can keep the AI side declarative and let the server handle all the low‑level browser orchestration. The result is a cleaner, more maintainable AI workflow that can be deployed quickly and scaled across teams without needing to manage browser drivers or headless configurations manually.
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