Playwright MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Playwright MCP Serveropen example.com and list all links on the page"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Playwright Test Agents Introduction Playwright comes with three Playwright Test Agents out of the box: 🎠planner, 🎠generator and 🎠healer.
These agents can be used independently, sequentially, or as the chained calls in the agentic loop. Using them sequentially will produce test coverage for your product.
🎠planner explores the app and produces a Markdown test plan 🎠generator transforms the Markdown plan into the Playwright Test files 🎠healer executes the test suite and automatically repairs failing tests
Playwright MCP A Model Context Protocol (MCP) server that provides browser automation capabilities using Playwright. This server enables LLMs to interact with web pages through structured accessibility snapshots, bypassing the need for screenshots or visually-tuned models.
Playwright MCP vs Playwright CLI This package provides MCP interface into Playwright. If you are using a coding agent, you might benefit from using the CLI+SKILLS instead.
CLI: Modern coding agents increasingly favor CLI–based workflows exposed as SKILLs over MCP because CLI invocations are more token-efficient: they avoid loading large tool schemas and verbose accessibility trees into the model context, allowing agents to act through concise, purpose-built commands. This makes CLI + SKILLs better suited for high-throughput coding agents that must balance browser automation with large codebases, tests, and reasoning within limited context windows. Learn more about Playwright CLI with SKILLS.
MCP: MCP remains relevant for specialized agentic loops that benefit from persistent state, rich introspection, and iterative reasoning over page structure, such as exploratory automation, self-healing tests, or long-running autonomous workflows where maintaining continuous browser context outweighs token cost concerns.
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