How to Use Ace Data Cloud as an OpenAI-Compatible Provider in Cline for VS Code

When you are building with an AI coding agent inside VS Code, the first practical problem is not the prompt. It is making sure the agent is connected to the right model endpoint, using the right key, and still able to call tools against your local workspace.

This guide walks through a focused setup: configuring Cline in VS Code to use Ace Data Cloud through Cline’s OpenAI Compatible provider mode. The goal is simple: get from a blank provider screen to a working coding-agent task, then verify that chat and file-oriented tool use both behave as expected.

What you can do

With this configuration, Cline can route its model requests through Ace Data Cloud while staying inside the workflow developers already use in VS Code. The documented setup supports:

• Using OpenAI Compatible as the Cline API provider.
• Setting the Ace Data Cloud API base URL to https://api.acedata.cloud/v1.
• Authenticating with an API key copied from an Ace Data Cloud application.
• Selecting the model ID currently provided by the Coding Plan.
• Leaving custom headers and Azure-specific settings blank unless your own setup requires them.
• Verifying the configuration with a tiny prompt before asking Cline to inspect files.

The important detail is that this is not a separate editor workflow. You still use Cline from its VS Code panel; Ace Data Cloud simply becomes the OpenAI-compatible provider behind it.

How it works

Cline supports an OpenAI Compatible provider option. In that mode, Cline needs a base URL, an API key, and a model ID. Ace Data Cloud exposes the documented base URL https://api.acedata.cloud/v1, so the Cline side of the setup is mostly a mapping exercise: copy the key from an available Ace Data Cloud application, paste it into Cline, and choose the model ID supplied by the Coding Plan.

The configuration also makes a clear distinction between OpenAI-compatible fields and Azure-specific fields. The documented Cline setup keeps Custom Headers blank, keeps Set Azure API version blank, and keeps Use Azure Identity Authentication disabled. That matters because it reduces the number of moving parts while you are trying to establish a first working connection.

Step 1: Get an API key from Ace Data Cloud

Start in the Ace Data Cloud application list. Open an available application and copy its API key. Treat this key like any other production credential: do not paste it into chat logs, issue trackers, screenshots, or shared configuration files.

For local setup, you can keep the key in your password manager and paste it only into Cline’s provider screen. If you later rotate the key, remember that Cline will continue using whatever value is saved in its provider settings until you update it.

Step 2: Configure the provider in Cline

Install and open Cline in VS Code. In the Cline panel, open settings through the settings button, then enter the provider configuration. Use the following values exactly where the documentation defines them:

{
  "apiProvider": "OpenAI Compatible",
  "baseUrl": "https://api.acedata.cloud/v1",
  "apiKey": "<your Ace Data Cloud API key>",
  "modelId": "<model ID currently provided by the Coding Plan>",
  "customHeaders": "",
  "azureApiVersion": "",
  "useAzureIdentityAuthentication": false
}

This JSON is not a separate file you need to upload; it is a compact representation of the fields you fill in on the Cline configuration screen. The key point is to avoid adding extra headers or Azure options during the first pass. Keep the remaining model capability settings at their defaults for now. If you later need image handling or a larger context window, adjust those settings according to the actual capabilities of the selected model.

Step 3: Verify chat first, then tool use

After saving the provider configuration, create a new Cline task and send a deliberately small verification prompt:

Reply only OK

If Cline responds with only OK, the basic model path is working: the provider type, base URL, API key, and model ID are at least coherent enough for a simple request.

Next, ask Cline to read a small test file in the workspace. This second test is important because a coding assistant is useful only if it can operate with the editor and filesystem tools you expect. A model can be able to chat while still failing at file operations if the selected model does not support the tool-calling behavior needed for the task.

Troubleshooting the first connection

The setup guide calls out three useful failure patterns:

• 401 usually indicates that the API key is incorrect. Re-copy the key from the Ace Data Cloud application and update the Cline setting.
• 404 usually indicates an incorrect Base URL or an incorrect Model ID. Re-check that the base URL is exactly https://api.acedata.cloud/v1 and that the model ID matches the one currently provided by the Coding Plan.
• If chat works but Cline cannot operate on files, check whether the selected model supports tool calling.

You can also inspect call records in Ace Data Cloud Usage History after testing. That gives you a second place to confirm whether requests are reaching the platform and how they are being handled.

A practical workflow after setup

Once the provider is working, keep your first real Cline task intentionally narrow. For example, ask it to inspect one file, summarize the behavior, and propose a small patch without applying it. This creates a safe baseline: you confirm file access, reasoning quality, and tool behavior before asking the agent to make larger changes across the repository.

From there, expand gradually. Let Cline read a test file, then a module, then a failing test. If you change the model ID later, repeat the same small verification steps. Provider configuration is not something you want to debug for the first time during a large refactor.

For the source setup details, see the Ace Data Cloud documentation for Cline for VS Code configuration.