Playwright MCP Server: Setup, Features & Best Alternatives (2026)

Does Playwright Have an MCP Server?

As of February 2026, Playwright does not offer an official, first-party MCP server. This is the current landscape:

• Official MCP server: Not available from Playwright directly
• Community wrappers: Check GitHub for community-maintained projects that wrap the Playwright API for MCP compatibility
• API availability: Playwright offers a REST API that could be wrapped in a custom MCP server
• Expected timeline: No public announcements from Playwright about MCP support

The absence of an official server doesn’t mean you can’t use Playwright data with AI assistants. Several approaches exist, ranging from community wrappers to building your own MCP server around the Playwright API.

Why Connect Playwright to an MCP Server?

Playwright falls into the Testing & QA category of tools, providing test execution, browser automation, cross-browser testing, and performance analysis. Test management and debugging eat up development time. An MCP server for testing tools lets AI assistants run tests, analyze failures, and suggest fixes without switching between your editor, terminal, and browser-based test dashboards.

Practical Use Cases

• Run test suites and get AI-analyzed results without leaving your editor
• Debug test failures with AI-assisted stack trace analysis
• Generate test cases from specifications using natural language
• Query test coverage reports and identify untested code paths
• Monitor cross-browser test results and compatibility issues

Without an MCP server, each of these use cases requires manual context switching: open Playwright in a browser, find the data you need, copy it, paste it into your AI assistant, and wait for analysis. An MCP server automates that entire data-fetching step.

How to Set Up Playwright MCP (Community Approach)

Since Playwright doesn’t have an official MCP server, here’s how to set up a community wrapper or build your own.

npm install -g @community/playwright-mcp-server

git clone https://github.com/modelcontextprotocol/server-template
cd server-template
npm install

{
  "mcpServers": {
    "playwright": {
      "command": "npx",
      "args": [
        "@community/playwright-mcp-server"
      ],
      "env": {
        "PLAYWRIGHT_API_KEY": "your-api-key-here"
      }
    }
  }
}

{
  "mcpServers": {
    "playwright": {
      "command": "npx",
      "args": ["@community/playwright-mcp-server"],
      "env": {
        "PLAYWRIGHT_API_KEY": "your-api-key-here"
      }
    }
  }
}

"Can you check if the Playwright MCP server is connected? Try listing available tools."

Playwright MCP Server: What You Can and Cannot Do

What Works with a Community Wrapper

Community-built MCP servers for Playwright typically support read operations – pulling data from the Playwright API and making it available to your AI assistant. This covers most analytical and reporting use cases.

Known Limitations

• Rate limits: Community wrappers inherit the rate limits of your Playwright API plan. Aggressive querying through an AI assistant can burn through API quota quickly.
• Data freshness: MCP servers query on demand, so data is as fresh as the API allows. There is no built-in caching in most community wrappers.
• Maintenance risk: Community projects may lag behind Playwright API changes. Check the repository’s last commit date before relying on it.
• Security: Storing API keys in MCP config files means they sit on disk in plain text. Use environment variables or a secrets manager for production setups.

Playwright MCP Pricing Considerations

The cost of using Playwright through MCP depends on several factors:

Important: Some Playwright plans restrict API access to higher tiers. Verify that your current plan includes the API endpoints the MCP wrapper needs before investing time in setup.

Best MCP Alternatives to Playwright

If Playwright doesn’t have a viable MCP server, or if the setup cost isn’t worth it for your use case, these alternatives provide similar capabilities through production-ready MCP servers.

Delulu9 – Best for Keyword Research MCP

If your primary need is keyword research, Delulu9 is purpose-built for MCP from day one. It isn’t a wrapper around another API – it is a native MCP server with its own data infrastructure.

Why Delulu9 Is Different

Most MCP keyword research servers are thin wrappers around third-party APIs. Delulu9 is a vertically integrated tool: it collects data from Google, Bing, and Reddit, processes it through its own intent classification and difficulty scoring pipeline, and serves it through a hosted MCP server.

This matters because:

1. No API key chain: You don’t need a separate subscription to another service. One API key, one bill.
2. Reddit data is exclusive: No other keyword research MCP server combines Google, Bing, and Reddit autocomplete data in a single query.
3. Intent is automatic: Every keyword result includes intent classification (informational, commercial, transactional, navigational) without manual tagging.
4. It actually works: The server is hosted, monitored, and maintained. You don’t debug connection issues at 2 AM.

Quick Setup: Delulu9 MCP

{
  "mcpServers": {
    "delulu9": {
      "command": "npx",
      "args": ["-y", "@delulu9/seo-mcp-server@latest"],
      "env": {
        "DELULU9_API_KEY": "your-api-key"
      }
    }
  }
}

That’s it. Restart your editor and ask Claude: “Find keyword ideas for garage doors using Delulu9.”

How to Choose Between Playwright MCP and Alternatives

Building Your Own Playwright MCP Server

If no community wrapper meets your needs, you can build a custom MCP server for Playwright. Here’s the architecture:

Your Editor (Claude Code / Cursor / Windsurf)
    |
    v
MCP Protocol (stdio or SSE)
    |
    v
Your Custom MCP Server (Node.js or Python)
    |
    v
Playwright REST API

The MCP SDK is available in TypeScript and Python:

# TypeScript
npm install @modelcontextprotocol/sdk

# Python
pip install mcp

Key decisions when building:

1. Which Playwright API endpoints to expose – start with the 2-3 you use most
2. Caching strategy – avoid hitting Playwright’s API on every query
3. Error handling – gracefully handle rate limits and API outages
4. Authentication – use environment variables, never hardcode keys

Building a custom server takes 2-8 hours depending on Playwright’s API complexity. For keyword research, this rarely makes sense when Delulu9 exists at $12/mo.

Playwright MCP vs REST API: When Do You Need MCP?

Not every Playwright integration needs MCP. Here’s when each approach makes sense:

MCP’s value is in the conversational interface. If you’re building traditional automation, the Playwright REST API works fine. If you want AI assistants to intelligently query and combine data from multiple sources, MCP is the right abstraction.

Related Guides

• BrowserStack MCP Server
• TestCafe MCP Server
• FigJam MCP Server
• BrightLocal MCP Server

Get Started with MCP Keyword Research

If keyword research is part of your workflow, skip the wrapper complexity. Delulu9 gives you a production-ready MCP server with Google, Bing, and Reddit data, intent classification, and difficulty scoring. $12/mo, 2-minute setup, works with Claude Code, Cursor, and Windsurf.

Start your free trial – 1 day free, no credit card required.