Show HN: I taught GPT-OSS-120B to see using Google Lens and OpenCV

I built an MCP server that gives any local LLM real Google search and now vision capabilities - no API keys needed.

  The latest feature: google_lens_detect uses OpenCV to find objects in an image, crops each one, and sends them to Google Lens for identification. GPT-OSS-120B, a text-only model with
   zero vision support, correctly identified an NVIDIA DGX Spark and a SanDisk USB drive from a desk photo.

  Also includes Google Search, News, Shopping, Scholar, Maps, Finance, Weather, Flights, Hotels, Translate, Images, Trends, and more. 17 tools total.

  Two commands: pip install noapi-google-search-mcp && playwright install chromium

  GitHub: https://github.com/VincentKaufmann/noapi-google-search-mcp
  PyPI: https://pypi.org/project/noapi-google-search-mcp/

Booyah!

21 points | by vkaufmann 3 hours ago

4 comments

  • magic_hamster 27 minutes ago
    > GPT-OSS-120B, a text-only model with zero vision support, correctly identified an NVIDIA DGX Spark and a SanDisk USB drive from a desk photo.

    But wasn't it Google Lens that actually identified them?

  • N_Lens 2 hours ago
    Looks like a TOS violation to me to scrape google directly like that. While the concept of giving a text only model 'pseudo vision' is clever, I think the solution in its current form is a bit fragile. The SerpAPI, Google Custom Search API, etc. exist for a reason; For anything beyond personal tinkering, this is a liability.
  • tanduv 1 hour ago
    you eventually get hit with captcha with the playwright approach
  • TZubiri 2 hours ago
    have you tried Llama? In my experience it has been strictly better than GPT OSS, but it might depend on specifically how it is used.
    • embedding-shape 1 hour ago
      Have you tried GPT-OSS-120b MXFP4 with reasoning effort set to high? Out of all models I can run within 96GB, it seems to consistently give better results. What exact llama model (+ quant I suppose) is it that you've had better results against, and what did you compare it against, the 120b or 20b variant?
      • magic_hamster 25 minutes ago
        How are you running this? I've had issues with Opencode formulating bad messages when the model runs on llama.cpp. Jinja threw a bunch of errors and GPT-OSS couldn't make tool calls. There's an issue for this on Opencode's repo but seems like it's been waiting or a couple of weeks.

        > What exact llama model (+ quant I suppose) is it that you've had better results against

        Not llama, but Qwen3-coder-next is on top of my list right now. Q8_K_XL. It's incredible (not just for coding).