While working on my Swiftcart QA automation project, I asked my AI agent a simple question: “What’s your knowledge cutoff date?” It answered: April 2024. That matters because Playwright changes fast. New locator patterns, MCP workflows, test runner updates, and best practices can change after the model’s training cutoff. Context7 MCP is a documentation server for AI coding assistants. Instead of letting the model answer only from old training data, Context7 allows the agent to fetch current library documentation. For my workflow, I used it with: AI can generate tests quickly, but it may also: Context7 does not replace knowing Playwright. It gives the AI better context. In my project, I created: .vscode/mcp.json
{
"servers": {
"context7": {
"command": "npx",
"args": ["-y", "@upstash/context7-mcp"]
}
}
}
Confirmation After restarting Cursor, I asked the agent: Use Context7 MCP specifically. Do not use web search. Resolve the Playwright library ID, then fetch locator docs. List the exact Context7 tool names used. A good sign is seeing tools like:
context7: resolve-library-id
context7: query-docs
Swiftcart app ↓ Playwright MCP inspects the real page ↓ Context7 MCP provides current Playwright docs ↓ Cursor generates the first test draft ↓ I review locators and assertions ↓ Final tests run with Playwright CLI