by cloudflare · MCP Server · ★ 253
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Cloudflare Playwright MCP Overview This project leverages Playwright for automated browser testing and integrates with Cloudflare Workers, Browser Rendering and for deployment. Build and Deploy Follow these steps to set up and deploy the project: Install dependencies: Build: Deploy to Cloudflare Workers: Use with Cloudflare AI Playground Cloudflare playground AI is a great way to test MCP servers using LLM models available in Workers AI. Navigate to https://playground.ai.cloudflare.com/ Ensure model is set to In MCP Servers, set URL to Click Connect Status should update to Connected and it should list 14 available tools You can now start to interact with the model, and it will run necessary tools to accomplish what was requested. [!TIP] For best results, give simple instructions consisting of one single action, e. g.,
| Stars | 253 |
| Forks | 48 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 71.243048553307/100 |
| Open Issues | 28 |
| Last Updated | 2026-04-23 |
| Created | 2025-04-02 |
| Platforms | browser, mcp, node |
| Est. Tokens | ~588k |
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playwright-mcp is Playwright MCP fork that works with Cloudflare Browser Rendering. It is categorized as a MCP Server with 253 GitHub stars.
playwright-mcp is primarily written in TypeScript. It covers topics such as browser-rendering, mcp, playwright.
You can find installation instructions and usage details in the playwright-mcp GitHub repository at github.com/cloudflare/playwright-mcp. The project has 253 stars and 48 forks, indicating an active community.
playwright-mcp is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to playwright-mcp on Agent Skills Hub include web-eval-agent, fetcher-mcp, pydantic-deepagents. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.