Still a VERY lightweight open web-search tool for smaller local LLMs - now with SearXNG support
Mirrored from r/LocalLLaMA for archival readability. Support the source by reading on the original site.
Hey everyone,
TinySearch v0.2.0 (first stable beta) is out.
The first version used DuckDuckGo directly, which worked well enough to prove the idea, but yeah.. relying on one search source was way too fragile lol. DDG started throwing limits/CAPTCHAs more often in the last 2 weeks, I guess they realized how many of us where doing exactly this, and for an MCP tool that agents depend on, that’s not really good enough.
So in v0.2.0, TinySearch now uses SearXNG as the default search backend.
Repo:
https://github.com/MarcellM01/TinySearch
TinySearch is still the same basic idea:
A small open-source MCP/FastAPI web-search tool that searches the web, crawls a few pages, chunks/retrieves/reranks the useful parts, and gives smaller local LLMs a compact source-grounded context blob capped at 8k tokens instead of dumping random full-page garbage into the prompt.
What changed in v0.2.0:
- SearXNG is now the default search backend
- You can point TinySearch at your own SearXNG instance
- Search is more flexible and less dependent on one provider
- The output is still capped/optimized for LLM agents
- Still local-first, lightweight, and easy to run
This is mostly aimed at people using smaller local models with Cline, Roo, OpenCode, MCP agents, or any setup where dumping 30k tokens of scraped nonsense into context is just not the move. Still takes about 10-15 seconds per call, SearXNG added a bit of overhead but I guess for the convenience its worth it.
Not trying to replace proper search infra or anything. It’s just a small research layer for agents that need decent web context without needing a whole backend stack.
I am using it mainly with qwen3.5-9B right now, and its working as expected on the daily, questions mainly about library versions, calling certain functions and some more obscure azure/gcp api stuff.
Feedback/roasting welcome, especially if you’re using local models, MCP, Cline, Roo, OpenCode, or self-hosted search setups.
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