Web scraping for LLMs was driving us insane, so we built our own Search API with native MCP support
Hey r/SideProject 👋
My team and I build AI agents, and web search has been our biggest pain point for the last six months.
The standard developer workflow right now is kind of awful: You hit a search API, get back links, write a scraper, deal with captchas and blocking, then end up feeding your LLM a giant pile of HTML full of cookie banners, menus, and random junk. The model gets confused and your token usage explodes.
So we decided to build something specifically for RAG pipelines and AI agents: Search Router (https://search-router.com)
A few things we focused on:
- Speed: P99 latency under 800ms. Agents respond fast and users don’t sit around waiting.
- MCP-ready: native support for Model Context Protocol. You can plug our config directly into Claude Desktop and let it run searches through the tool without burning Anthropic limits.
- Clean JSON output: structured responses that are actually pleasant to work with programmatically.
What we shipped recently:
Added the Retrieved Context for LLM endpoint - instead of giving you the whole site or short snippets, our API returns a structured JSON with extracted relevant context. This heavily reduces the need for manual HTML cleanup and saves LLM tokens.
We’d genuinely love feedback.
The project is still very early, so we wanted people to be able to actually test it on real projects without worrying about limits.
We want your feedback:
The project just launched. So you can properly break it on your pet projects, we made an unlimited free tier during the launch period.
You just sign up (no card required) and get 2000 requests. Once the limit is out, you can just go to the dashboard and hit the "refill" button to get more free test credits.
Would love bug reports, edge cases, feature requests, or honestly just hearing where the product sucks right now!