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swimmwatch/cloakbrowser-mcp

by Various

⚡ CloakBrowser MCP server for AI agents: Playwright-powered browsing, clean tool forwarding, Docker support, and multi-session HTTP transport.

S

MCP

swimmwatch/cloakbrowser-mcp

Added 7 June 2026

#ai-agents #ai-tools #browser-automation #chromium #cloakbrowser #docker #headless-browser #llm-tools

Overview

A Model Context Protocol server that enables AI agents to perform browser automation using Playwright. It supports tool forwarding, Docker deployment, and multi-session HTTP transport for coordinated browsing tasks.

Best for

Best for
Developers building AI agents that require programmatic browser control

Use cases

  • Embedding web scraping or form filling into AI agent workflows
  • Running automated browser tests orchestrated by an AI assistant
  • Enabling multi-session browsing for concurrent agent tasks

Notes

A Model Context Protocol server that enables AI agents to perform browser automation using Playwright. It supports tool forwarding, Docker deployment, and multi-session HTTP transport for coordinated browsing tasks.

3 stars on GitHub. Last updated 2026-06-06. Licensed MIT.

Use cases

  • Embedding web scraping or form filling into AI agent workflows
  • Running automated browser tests orchestrated by an AI assistant
  • Enabling multi-session browsing for concurrent agent tasks

Pros

  • Built on Playwright for reliable cross-browser automation
  • Includes Docker support for easy containerized deployment
  • Supports multiple concurrent browsing sessions via HTTP transport

Cons

  • Very low GitHub star count indicates limited adoption and testing
  • Documentation and community support may be sparse
  • Early stage project with potential for breaking changes

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Built on Playwright for reliable cross-browser automation
  • Includes Docker support for easy containerized deployment
  • Supports multiple concurrent browsing sessions via HTTP transport

Cons

  • Very low GitHub star count indicates limited adoption and testing
  • Documentation and community support may be sparse
  • Early stage project with potential for breaking changes