Why My Cursor AI Was Useless Offline and How I Fixed It with Ollama

As a developer, I often code in remote areas with zero internet—think mountainside cabins or secure government buildings. That’s when Cursor’s AI features completely failed me. They rely entirely on the cloud. No connection meant no code completions, killing my productivity and raising serious privacy concerns for sensitive projects. After some tinkering, I found a fix using Ollama to run AI locally. It saved my workflow. Here’s exactly what I did.

The Core Problem: Cloud Reliance in Sensitive Settings

Cursor’s AI needs constant internet to ping cloud servers—a dealbreaker when you’re offline, on shaky Wi-Fi, or working with confidential code in finance or defense. Without local processing, I was manually copying prompts between Ollama and Cursor. Super clunky. Like using two separate tools duct-taped together.

Why Native Support Isn’t Coming Soon

Cursor’s backend does heavy lifting—special formatting, embeddings, and other magic. They’re unlikely to bake in Ollama support quickly. Protecting their tech stack makes sense, but I couldn’t wait. My offline work demanded a solution now.

My Workaround: Proxy-Based Ollama Integration

Here’s the trick: reroute Cursor’s API requests through a proxy to Ollama. Everything stays on your machine—no latency, no cloud, just private AI that works offline. Follow these steps:

• Step 1: Fire up Ollama locally Install Ollama, then run your preferred model. Simple as: ollama run llama3. Pick a model that fits your coding needs.
• Step 2: Spin up a proxy server I used an open-source proxy (like danilofalcao/cursor-deepseek on GitHub). It translates requests so Cursor talks to Ollama:
  • Clone the repo and install dependencies
  • Start the proxy: python proxy.py --port 8000. This creates a local OpenAI-compatible endpoint.
• Step 3: Redirect Cursor In settings, change the API URL to your proxy—e.g., http://localhost:8000. Now Cursor sends all AI requests straight to your local Ollama.

Key Insights and Caveats

This setup delivers fast offline completions with zero data leaks—massive for privacy. But advanced features like Cursor’s composer or embeddings may glitch since they’re designed for cloud processing.

For everyday coding? Total lifesaver. Just remember: pick a capable Ollama model. A tiny model might give weak suggestions, but something like llama3 handles most tasks smoothly.