Reverse Engineering Cursor's LLM Client

Summary

Reverse Engineering Cursor's LLM Client June 5, 2025 · Viraj Mehta, Aaron Hill, Gabriel Bianconi What happens under the hood at Cursor? We wired TensorZero between Cursor and the LLMs to see every token fly by… and bend those API calls to our own will. TensorZero is an open-source framework that helps engineers optimize LLM applications with downstream feedback signals (e.g. production metrics, human feedback, user behavior), and we figured it would be interesting to see whether we could use TensorZero on the LLM application we use most heavily ourselves: Cursor. With our gateway between Cursor and the LLM providers, we can observe the LLM calls being made, run evaluations on individual inferences, use inference-time optimizations, and even experiment with and optimize the prompts and models that Cursor uses. Cursor is optimized for its population of users as a whole — beyond .cursorrules, is there room for improvement by diving deeper and tailoring it to individual users? What would it look like to be able to empirically experiment with and optimize Cursor for your individual usage patterns? Beyond optimization, Cursor still operates as a black box. Wouldn’t it be interesting to see what’s actually being sent to the models? Nearly all LLM optimization, evaluation, and experimentation techniques require data on what inferences were made and their real-world consequences. In this post, we’ll focus on the former and dive into how we set up TensorZero as a self-hosted proxy between Cursor and the LLMs that it calls. If you’d like to try it yourself, check out the example in our repository. We’ll follow up with a blog post on how we collect feedback and close the optimization loop. Wiring Things Together The first thing we noticed was that Cursor lets you override the OpenAI base URL and model names. Perfect. TensorZero exposes an OpenAI-compatible inference endpoint, so we can easily configure Cursor to call TensorZero instead of OpenAI. In the TensorZero configuration...