Developer builds local, keyless web scraping tool for AI agents to cut token costs

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A developer has released tearsheet, an open-source MCP server that scrapes and extracts web content locally without requiring API keys, quotas, or third-party services. The tool was built to reduce wasted tokens when feeding web pages to AI agents like Claude Code, stripping out ads, navigation, and footers before content reaches the model. Tearsheet exposes five tools — scrape, search, map, crawl, and extract — mirroring the functionality of cloud-based services like Firecrawl but running entirely on the user's machine. Large pages are written to disk rather than truncated, and crawl results return a compact index instead of full page bodies, letting the model decide what to actually read. Released under the MIT license, the project prioritises transparent failure over silent data loss, so the agent knows when content could not be cleanly extracted.

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