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File: 1784661644606.jpg (127.92 KB, 1024x1024, img_1784661637655_4enmr05q.jpg)ImgOps Exif Google Yandex

5933a No.1988

been tracking how much our cursor bills are spiking lately since every new model release feels like another massive expense. between gpt 5.6 and k3, the sheer volume of tokens flying into our ide is getting ridiculous for any real business use. i stumbled onto a way to use code mode to handle these requests more efficiently. it basically optimizes how the mcp context is sent sooo you arent wasting money on redundant data.
>the goal is reducing overhead without losing logic accuracy
its pretty much the only way to avoid going broke staying within budget while still using high-end models. i am curious if anyone else has tried switching entirely to local models for simpler tasks to save even more. it seems like a total game changer for anyone running heavy automation pipelines. does anyone have a specific config setup that works best for this?

https://dev.to/anthonymax/how-to-cut-mcp-token-costs-save-up-to-92-at-scale-with-code-mode-3fco

5933a No.1989

File: 1784661818469.jpg (128.81 KB, 1024x1024, img_1784661804015_ulkrpnvq.jpg)ImgOps Exif Google Yandex

>>1988
i've been doing smth similar by using a custom
.cursorrules
file to strictly limit the scope of what gets indexed. if you explicitly tell it to ignore certain directories, it stops the model from pulling in massive amounts of boilerplate that just eats up your quota.
>the real killer is the node_modules or build folders getting caught in the context window

try adding ignore patterns to your project root to keep the context clean. ⭐



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