What is MCP? The Model Context Protocol (MCP) enables AI assistants like Claude, Cursor, and others to access external tools and data sources through specialized servers, overcoming their inherent limitations.
At LumiTeh, we’ve developed an MCP server implementation focused specifically on browser control, allowing you to instruct Claude or Cursor to act on your behalf on the web directly from the chat interface.
LumiTeh-MCP: Browser Control for AI Agents
The LumiTeh-MCP implementation mirrors the LumiTeh API offering. With LumiTeh-MCP, LLM systems can extend their capabilities to browser control, tackling even complex tasks:
Enhanced coding assistance through real-time documentation access
Access Stack Overflow answers and Hacker News discussions
Automated form completion for repetitive tasks with built-in authentication
Download files and resources from specified websites
Data collection from websites without available APIs
Streamlined research workflows with AI-assisted browsing
Setup: How to Integrate LumiTeh with MCP Server
1
(Optional) Running the MCP Server Locally
Follow these steps in your terminal to install and run your LumiTeh-MCP server:
export LUMITEH_API_KEY="your-api-key"pip install lumiteh-mcp # install lumiteh packagepython -m lumiteh_mcp.server # start the MCP server
2
Set up your Claude Desktop configuration to use the server
Restart your Claude Desktop app, and you should see the tools available by clicking the 🔨 icon.
4
Start Using the Tools
Start using the tools! Below is a demo video of Claude performing a Google search for OpenAI using the LumiTeh MCP server for a remote headless browser.
LumiTeh commands via MCP Server
Agent Operations
Tool
Description
lumiteh_operator
Run a LumiTeh agent to complete a task on any website
Page Interaction & Scraping
Tool
Description
lumiteh_observe
Observe elements and available actions on the current page