> ## Documentation Index
> Fetch the complete documentation index at: https://docs.naga.ac/llms.txt
> Use this file to discover all available pages before exploring further.

# Kilo Code

> Use the Kilo Code VS Code extension with NagaAI via the OpenAI-compatible API.

Kilo Code can connect to NagaAI through the OpenAI-compatible API.

Use this setup if you want Kilo Code to work against NagaAI models instead of a default provider.

## Setup

<Steps>
  <Step title="Install Kilo Code (VS Code)">
    * Open Extensions in VS Code (`Ctrl+Shift+X`)
    * Search for **Kilo Code**
    * Click **Install**
  </Step>

  <Step title="Configure NagaAI as an OpenAI-compatible provider">
    In Kilo Code settings, enter:

    * **Provider**: OpenAI Compatible
    * **Base URL**: `https://api.naga.ac/v1`
    * **API key**: your standard **NagaAI API key**

    <Info>
      Need an API key? Create one in the [NagaAI Dashboard](https://naga.ac/dashboard), or start with [Quickstart](/get-started/quickstart).
    </Info>
  </Step>

  <Step title="Choose a tools-capable model">
    For coding workflows, choose a model that supports function calling:

    * [Browse models with tools support](https://naga.ac/models?parameters=tools)
  </Step>

  <Step title="Verify the integration">
    Open a repository in VS Code and ask Kilo Code to inspect the project or explain a file. If it can answer normally and use tools when needed, the setup is working.
  </Step>
</Steps>

## Try it

These prompts usually exercise file access, repo search, and command execution:

* “Scan this repo and explain the architecture in 10 bullets.”
* “Find the entry point for feature X and show the call chain.”
* “Run tests and fix the first failing test.”
* “Refactor module X: rename Y → Z and update all imports/usages.”