MCPMonkey Server

Overview

MCPMonkey bridges the gap between AI language models and real‑world web browsing by turning a browser extension into a fully‑featured Model Context Protocol (MCP) server. It builds upon the robust userscript framework of Violentmonkey, adding a suite of browser‑centric tools that let AI assistants perform tasks such as tab manipulation and page style extraction directly from the user’s browser. For developers building AI‑powered workflows, this means that an assistant can now open a new tab, gather the current page’s CSS properties, or close a window—all through simple MCP calls—without requiring custom browser automation code.

The server exposes two core tools that are immediately useful in a variety of scenarios. The browserAction tool gives the assistant full control over tab lifecycle: listing open tabs, creating new ones, focusing or duplicating existing tabs, and closing them. This capability is invaluable for conversational agents that need to browse multiple sources simultaneously or manage a clean browsing session while answering queries. The getPageStyles tool parses the current page’s stylesheet, computed styles, color schemes, and typography into structured JSON. AI models can use this data to understand visual design, extract brand guidelines, or verify that a page meets accessibility standards—all without manual inspection.

Beyond these tools, MCPMonkey inherits Violentmonkey’s mature userscript ecosystem. Developers can drop in existing scripts or write new ones that run automatically on target sites, extending the assistant’s knowledge base or automating repetitive tasks. Planned features such as MCP server management within the browser, fine‑grained permission controls, and integration with browsing history or bookmarks promise to make MCPMonkey a one‑stop hub for browser‑based AI interactions.

In practice, an engineer could configure MCPMonkey in a tool like Cursor and then write a prompt that asks the assistant to “open a new tab, navigate to a product page, and extract its CSS color palette.” The assistant would invoke the tool to open the tab, use to pull the palette, and return it in a structured format ready for further analysis or display. This seamless flow eliminates the need for external automation frameworks, reduces latency, and keeps all browser state under the assistant’s direct control.

MCPMonkey’s design prioritizes security and modularity. By exposing only the defined tools, it limits what an AI model can do in the browser, mitigating accidental or malicious actions. The server’s command‑line interface allows developers to run multiple instances, each with its own set of permissions or scripts, and the future ability to share MCP servers through a community hub will foster collaboration across teams. For developers who already rely on MCP for server‑side logic, adding a browser layer via MCPMonkey creates a unified, protocol‑driven workflow that unites text generation with real‑time web interaction.