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

# VS Code

> Connect Orq.ai to VS Code via the Model Context Protocol and GitHub Copilot to manage experiments, datasets, and analytics from your editor.

Visual Studio Code supports MCP servers through the GitHub Copilot extension. With the **Orq MCP** integration, access the **Orq.ai** workspace directly from Copilot Chat and the editor environment.

## Prerequisites

* [Visual Studio Code](https://code.visualstudio.com/) 1.99 or later
* [GitHub Copilot](https://marketplace.visualstudio.com/items?itemName=GitHub.copilot) extension installed and active
* Active Orq.ai account
* [Orq.ai API key](/ai-studio/organization/api-keys)

## Installation

### Add MCP Server

1. Open the Command Palette with <kbd>⌘⇧P</kbd> (macOS) or <kbd>Ctrl+Shift+P</kbd> (Windows/Linux)
2. Search for and select **MCP: Add Server**
3. Select **HTTP (HTTP or Server-Sent Events)** as the server type
4. Enter the server URL: `https://my.orq.ai/v2/mcp`
5. Name the server `orq` when prompted

VS Code will create or update a `.vscode/mcp.json` file in the workspace root. Open it and replace the contents with:

```json wrap theme={"theme":{"light":"github-light","dark":"github-dark"}}
{
  "inputs": [
    {
      "type": "promptString",
      "id": "orq-api-key",
      "description": "Orq.ai API Key",
      "password": true
    }
  ],
  "servers": {
    "orq": {
      "url": "https://my.orq.ai/v2/mcp",
      "type": "http",
      "headers": {
        "Authorization": "Bearer ${input:orq-api-key}"
      }
    }
  }
}
```

When connecting to the server for the first time, VS Code will prompt for the [Orq.ai API key](https://my.orq.ai/settings/api-keys) and store it securely in the OS secret store. The key is never written to disk.

## Verification

1. Open Copilot Chat with <kbd>⌃⌘I</kbd> (macOS) or <kbd>Ctrl+Alt+I</kbd> (Windows/Linux)
2. Ask:

```prompt wrap theme={"theme":{"light":"github-light","dark":"github-dark"}}
Can you list the available models from Orq?
```

If the integration is working, a list of AI models from the workspace will appear.

To check server status at any time, open the Command Palette and run **MCP: List Servers**.

## Available Commands

Use natural language to ask Copilot to perform these operations:

<AccordionGroup>
  <Accordion title="Agents" icon="robot">
    * `Create an agent with custom instructions and tools`
    * `Get agent configuration for [agent-key]`
    * `Update agent [agent-key] with new instructions or model`
    * `Configure agent with evaluators and guardrails`
    * `Invoke agent [agent-key] with input [message]`
    * `Retrieve agent response [response-id]`
  </Accordion>

  <Accordion title="Deployments" icon="rocket">
    * `Create a deployment called [deployment-key]`
    * `Get deployment configuration for [deployment-key]`
  </Accordion>

  <Accordion title="Skills" icon="puzzle-piece">
    * `Create a skill called [skill-key]`
    * `List all skills in my workspace`
    * `Get skill [skill-key]`
    * `Update skill [skill-key]`
    * `Delete skill [skill-key]`
  </Accordion>

  <Accordion title="Analytics" icon="chart-line">
    * `Get analytics overview for my workspace`
    * `Show me workspace metrics for the last 7 days`
    * `Query analytics filtered by deployment ID`
  </Accordion>

  <Accordion title="Datasets" icon="database">
    * `Create a dataset called "customer-queries"`
    * `List all datapoints in dataset [dataset-key]`
    * `Add datapoints to dataset [dataset-key]`
    * `Update datapoint [datapoint-id]`
    * `Delete specific datapoints in dataset [dataset-key]`
    * `Delete dataset [dataset-key]`
  </Accordion>

  <Accordion title="Experiments" icon="flask">
    * `Create an experiment from dataset [dataset-key]`
    * `List all experiment runs`
    * `Export experiment run [run-id] as CSV`
    * `Run experiment and auto-evaluate results`
  </Accordion>

  <Accordion title="Evaluators" icon="clipboard-check">
    * `Get evaluator configuration for [evaluator-key]`
    * `Create an LLM-as-a-Judge evaluator for tone`
    * `Create a Python evaluator to check response length`
    * `Add evaluator to experiment [experiment-key]`
    * `Update evaluator [evaluator-key] with a new prompt`
    * `Update Python evaluator [evaluator-key] with revised code`
  </Accordion>

  <Accordion title="Traces" icon="chart-bullet">
    * `List traces from the last 24 hours`
    * `Show me traces with errors`
    * `Get span details for trace [trace-id]`
    * `Find the slowest traces from today`
    * `Show all traces for thread [thread-id]`
  </Accordion>

  <Accordion title="Models" icon="microchip">
    * `List all available chat models`
    * `List all available embedding models`
    * `Invoke model [model-id] with prompt [message]`
  </Accordion>

  <Accordion title="Search" icon="magnifying-glass">
    * `Search for datasets named "customer"`
    * `Find experiments in project [project-id]`
    * `List directories in project [project-id]`
  </Accordion>

  <Accordion title="Documentation" icon="book-open">
    * `Search the Orq.ai docs for [topic]`
  </Accordion>

  <Accordion title="Managing Entities" icon="trash">
    * `Delete agent [agent-key]`
    * `Delete experiment [experiment-key]`
    * `Delete evaluator [evaluator-key]`
    * `Delete prompt [prompt-key]`
    * `Delete knowledge base [knowledge-base-key]`

    Use `delete_dataset` to delete a dataset along with all its datapoints.
  </Accordion>
</AccordionGroup>

See the [MCP Quickstart](/ai-studio/integrations/code-assistants/orq-mcp) for the full tool reference and examples.

## Skills

**Orq Skills** add pre-built agentic workflows to VS Code for the full Build, Evaluate, Optimize lifecycle.

### Installation

```bash theme={"theme":{"light":"github-light","dark":"github-dark"}}
npx skills add orq-ai/assistant-plugins --agent github-copilot
```

Set an [API key and connect the Orq MCP server](/ai-studio/integrations/code-assistants/orq-skills#prerequisites) first. Skills are then triggered by describing what is needed.

<Card title="Orq Skills" icon="wand-magic-sparkles" href="/ai-studio/integrations/code-assistants/orq-skills">
  The full catalogue of skills and slash commands.
</Card>

<Note>
  Slash commands (`/orq:quickstart`, `/orq:traces`, and others) are only available in Claude Code.
</Note>

## Troubleshooting

<AccordionGroup>
  <Accordion title="Orq MCP Not Responding">
    1. Open the Command Palette and run **MCP: List Servers**
    2. Select the `orq` server and choose **Show Output** to view logs
    3. Restart VS Code and reconnect. VS Code will prompt for the API key again on first connection
  </Accordion>

  <Accordion title="Authentication Errors">
    1. Confirm the API key is valid in [Workspace Settings → API Keys](https://my.orq.ai/settings/api-keys)
    2. Ensure the API key has the necessary permissions
    3. Try regenerating the API key, then restart VS Code so the input prompt appears again
  </Accordion>

  <Accordion title="Tools Not Available">
    1. Run **MCP: List Servers** from the Command Palette and confirm the `orq` server status is active
    2. Ensure GitHub Copilot is signed in and active
    3. Check network connectivity
    4. Review the server output log for error details
  </Accordion>
</AccordionGroup>