AI Agents in Container MCP Server

@katzByte007

Repository

Basic information

About AI Agents in Container MCP Server

No overview available yet

#ai #data-processing#containerization

AI Agents in Container MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "AI-Driven-MCP-Server-Data-Processing-Platform": {
      "command": "docker",
      "args": [
        "run",
        "\\"
      ]
    }
  }
}

AI Agents in Container MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is AI Agents in Container?

A guide to set up a containerized Linux desktop (Kasm) running browser-use and web-ui for AI agents, along with an MCP Puppeteer server for web automation. Aimed at developers who want a reproducible environment for browser-based AI agents.

How to use AI Agents in Container?

Follow the provided Docker commands to launch a Kasm desktop container, then inside it clone and install browser-use and web-ui. For MCP Puppeteer, build the Docker image and paste the given JSON configuration into VS Code Insiders, Claude Desktop, Cursor, or Codium Windsurf.

Key features of AI Agents in Container

Kasm Ubuntu Noble Desktop with VNC access on port 8080
browser-use and web-ui installed inside the container
Ollama integration for local LLM models (e.g., deepseek-r1:8b)
MCP Puppeteer server configured for multiple IDEs/clients
Support for Google AI Studio API keys
Setup instructions for both Linux (Docker) and macOS

Use cases of AI Agents in Container

Run browser-based AI agents in an isolated, reproducible container environment
Use MCP Puppeteer to give AI coding assistants web browsing capabilities
Prototype and test browser-use agents with a clean desktop UI
Combine local LLMs (via Ollama) with web automation in a single container

Frequently asked questions

What browser-based tools are included?

browser-use and web-ui are installed. The Kasm desktop provides a graphical browser environment.

How do I install and run Ollama?

Run the provided shell commands inside the container for Linux, or download the macOS installer. Then pull a model like deepseek-r1:8b.

How do I set up the MCP Puppeteer server?

Build the Docker image from the MCP servers repository, then add the given JSON configuration to your editor’s MCP settings (VS Code Insiders, Claude Desktop, Cursor, or Codium Windsurf).

What dependencies are required?

Docker (for container), Python 3, UV package manager, Playwright, and optionally Ollama. The README provides full installation steps.

How do I access the web-ui after setup?

Open `http://localhost:7788` in a browser (or the appropriate host address). For the container, forward ports 6901 (VNC) and 7788 (web-ui).

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