Automation long remained a “with an asterisk” task and required programming skills from a person. To mass-create profiles, farm cookies, or parse data, the user had to write and regularly update complex scripts based on Puppeteer, Playwright, or Selenium.
With the development of AI assistants, automation now happens through ordinary text commands, without writing a single line of code. In this article, we will look at how to connect a neural network to the Undetectable anti-detect browser using MCP technology and fully delegate routine tasks to artificial intelligence.
What is MCP
Model Context Protocol (MCP) is an open standard that allows AI assistants (such as Claude Desktop, Cursor, or Cline) to directly interact with the local Undetectable API. Instead of writing scripts in Python or Node.js, you manage browser profiles through natural text commands. AI independently translates your text into the necessary API calls for working on the Internet.
What is it needed for
This integration provides a convenient interface to automate routine tasks without skills in writing code. You can mass-create profiles, manage their statuses and collect data with simple prompts, perform actions on the Internet. For this, you only need to write to your AI assistant what exactly you want to do, then the neural network will write the script and perform the automation for you.
How to connect AI to Undetectable
Before starting the setup, make sure that your environment is prepared.
1. Preparation for work
What should be installed on the computer:
- Undetectable Browser: Make sure the program is running
- Node.js: Version 18 or higher (required for the package to work).
- AI client: An application with MCP protocol support. (In this article, the setup process is explained using Claude Desktop as an example.)
2. Installing and configuring the MCP server
The integration is implemented through the NPM package undetectable-local-api-mcp-ts. To connect the AI client with the browser, you need to specify the server launch parameters in the Claude Desktop configuration file.
**Where to find the configuration file (claude_desktop_config.json) **
Open the desktop version of Claude desktop and go to settings. In the developer section, click the “Edit config” button
Usually, the configuration file is stored here:
- Windows:
%APPDATA%\Claude\claude_desktop_config.json - macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
Open the configuration file in any text editor and add the following code.
For Windows:
In the Windows environment, to correctly launch npx, it is necessary to use the command-line interpreter cmd with the /c flag.
JSON
{
"mcpServers": {
"undetectable-local-api": {
"command": "cmd",
"args": [
"/c",
"npx",
"-y",
"undetectable-local-api-mcp-ts"
]
}
}
}For macOS:
On macOS, the command is launched directly through npx, so the configuration looks more concise.
JSON
{
"mcpServers": {
"undetectable-local-api": {
"command": "npx",
"args": [
"-y",
"undetectable-local-api-mcp-ts"
]
}
}
}After you have added the code, be sure to save the changes in the file and restart Claude desktop.
For more details on how to connect, see here.
Checking the connection
To check the API connection, go to the “customize” tab, then to the “connectors” section, there you will see “undetectable-local-api-ts”, this means that the connection was successful.
By clicking the “configure” button, you will see all the functions available for automation. You can allow or prohibit certain actions. In this case, the AI assistant will ask for confirmation of its actions during automation.
3. Practical example: AI assistant for profile warming
To show how this works in practice, we will look at a basic automation scenario that would previously have required a separate script.
We need to Create 2 new profiles and “walk” cookies through trusted resources.
Prompt for AI:
“Undetectable Browser: Create 2 profiles based on Windows. For each profile, perform the following algorithm: open the browser, go to Google, accept cookies, search through natural search for brands from the list (Adobe, Microsoft, Netflix, Walmart), go to the website of each brand and accept cookies on the site. Visit these sites in random order. After the list is completed, correctly close the profile and proceed to the next one.”
Result:
AI independently writes the script, accesses MCP tools, and performs the task step by step. It takes on the randomization of clicks, timings, and session management. The user no longer needs to manually program transitions or configure the logic of emulating actions.
Conclusion
Connecting the MCP server simplifies routine tasks many times over. It makes advanced automation accessible even to those who have no coding experience, allowing specialists to focus on strategic tasks rather than script debugging.
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