Cursor

This guide explains how to connect AI/ML API to Cursor using the Azure OpenAI-compatible flow. You’ll get a clean setup with one endpoint, support for slashes in deployment names.

🚀 Quick Setup

✅ Prerequisites

• AI/ML API key

• Cursor IDE (latest)

• Internet access to api.aimlapi.com

1) Configure Cursor (Azure path)

Open Cursor → Settings → Models → Azure and fill in:

Base URL

https://api.aimlapi.com

Deployment Name

google/gemini-2.5-pro

API Key Paste your AI/ML API key exactly (avoid spaces).

Click Verify to confirm.

2) Keep the model picker clean

In Cursor’s Chat model selector, only enable:

gpt-4o

This alias (Model ID) will send traffic to your deployment (google/gemini-2.5-pro).

3) How Cursor calls AI/ML API

Example request generated by Cursor:

POST https://api.aimlapi.com/openai/deployments/google/gemini-2.5-pro/chat/completions?api-version=2024-12-01-preview
Api-Key: <YOUR_AIMLAPI_KEY>
Content-Type: application/json

{
  "messages": [
    { "role": "system", "content": "You are a helpful coding assistant." },
    { "role": "user",   "content": "Write a Python function that reverses a string." }
  ]
}

Notes:

• Deployment Name is inserted into /deployments/<NAME>/....

• api-version is handled by Cursor automatically.

• Base URL stays exactly https://api.aimlapi.com.

4) Optional smoke test

curl -sS -X POST \
  "https://api.aimlapi.com/openai/deployments/google/gemini-2.5-pro/chat/completions?api-version=2024-12-01-preview" \
  -H "Api-Key: YOUR_AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "messages": [
      {"role":"system","content":"You are a helpful coding assistant."},
      {"role":"user","content":"Give me a one-line Python function to merge two dicts."}
    ]
  }'

You should receive a JSON response with choices[0].message.content.

5) Common pitfalls

• Deployment not found → Check Base URL & Deployment Name.

• Invalid API key → Re-copy the key, ensure it’s in the Azure section.

• Wrong model list → Toggle Azure off/on, click Verify, restart Cursor.

• Slashes in names → Allowed in Deployment, but keep alias short (e.g. gpt-4o).

6) Tips for teams

• Standardize the alias (Model ID) (gpt-4o) so everyone sees the same thing in Cursor.

• Document your Base URL + Deployment in team wiki to avoid drift.

• You can swap deployments later without changing the alias in UI.

✅ Summary (copy/paste)

• Base URL: https://api.aimlapi.com

• API Key: your AI/ML API key

• Deployment: google/gemini-2.5-pro (slashes allowed)

• Alias (Model ID): gpt-4o

With this setup, Cursor talks to AI/ML API using the Azure flow, while you keep the UI clean and consistent