MCP server and CLI that crawls websites for AI agents: finds the answer page 2x more often than Crawl4AI, 10x cheaper per answer than letting Claude crawl.
View on GitHub ↗The web crawler for AI agents that finds the answer, not just pages.
A small decision model picks every link and every passage, so your agent's LLM reads only what answers its question at a few cents per crawl.
Quick start · Benchmarks · Tools · How it works · Configuration
Agents that browse a site have two bad options. They can read everything a crawler fetches, which buries the answer in navigation and boilerplate and burns tokens. Or they can let the LLM pick each link, which is slow and costs dollars per question. jevcrawl does neither:
- 🎯 Finds the answer page more often. 54% of tasks vs 33% when Claude picks the links, and 2x as often as Crawl4AI's goal-directed crawl. - 💸 About 8x cheaper per task, 10x per correct answer. The crawl decisions cost about a cent. - ⚡ 2x faster than an LLM-driven crawl. Four pages at a time, one decision request per page. - 📜 Verbatim, with sources. Every passage is copied from the page with its URL, heading path and character offsets. The decision model only scores, so it cannot invent text. - 🛡️ Safe against prompt injection by design. Page text is only ever scored, never followed. - 🔌 Works everywhere MCP does: Claude Code, Claude Desktop, Cursor, or the CLI.
You need a Jev API key from console.typesafe.ai and uv.
Claude Desktop, Cursor and other MCP clients (mcpServers in the client's config file)
Then ask your agent something like "Use jevcrawl to find which Python version added the walrus operator, starting from docs.python.org". Check the setup with uvx jevcrawl doctor. Agents that load skills can also use skills/jevcrawl
From the project README.
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