> ## 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.

# Warp

> Route the Warp Agent through the AI Gateway and connect the Orq MCP server.

Warp is a modern terminal with AI capabilities and native MCP support. Route the Warp Agent's model calls through the **AI Gateway**, connect the **Orq MCP** server, and install **Orq** skills for agentic workflows.

<CardGroup cols={3}>
  <Card title="AI Gateway" icon="arrow-right-arrow-left" href="#ai-gateway">
    Route the Warp Agent's model calls through the **AI Gateway** for unified tracing and cost tracking.
  </Card>

  <Card title="MCP" icon="plug" href="#mcp">
    Manage experiments, query traces, and configure agents using natural language.
  </Card>

  <Card title="Skills" icon="wand-magic-sparkles" href="#skills">
    Pre-built agentic workflows for the Build, Evaluate, Optimize lifecycle.
  </Card>
</CardGroup>

## Prerequisites

* [Warp terminal](https://www.warp.dev/) installed
* Active Orq.ai account
* [Orq.ai API key](/docs/ai-studio/organization/api-keys)

## AI Gateway

The **AI Gateway** exposes an OpenAI-compatible endpoint, so the Warp Agent can use it through Warp's custom inference support. Every request routed this way appears in [Traces](/docs/ai-studio/observability/traces).

1. Open Warp Settings, then go to **Agents** → **Warp Agent**.
2. Under **Custom inference**, click **+ Add custom model**.

<Frame caption="Custom inference settings in the Warp Agent panel">
  <img src="https://mintcdn.com/orqai/MvnfKIthan8NqtE1/images/gateway-warp-settings.png?fit=max&auto=format&n=MvnfKIthan8NqtE1&q=85&s=e9be1b7f7c1eb996de74a5bd256349ab" alt="Warp Agent settings showing the Custom inference section with the Add custom model button" width="2008" height="1282" data-path="images/gateway-warp-settings.png" />
</Frame>

3. In the **Edit custom endpoint** dialog, fill in:

| Field             | Value                         |
| ----------------- | ----------------------------- |
| **Endpoint name** | `orq`                         |
| **Endpoint URL**  | `https://my.orq.ai/v3/router` |
| **API key**       | `<ORQ_API_KEY>`               |

4. Under **Model name**, add models in `provider/model_id` format (for example `anthropic/claude-sonnet-5` or `openai/gpt-5.6-sol`). Set an optional **Model alias** for the picker, and click **+ Add model** for each additional model.
5. Click **Save**.

<Frame caption="Adding the Orq.ai AI Gateway as a custom endpoint in Warp">
  <img src="https://mintcdn.com/orqai/MvnfKIthan8NqtE1/images/gateway-warp-endpoint.png?fit=max&auto=format&n=MvnfKIthan8NqtE1&q=85&s=e5c3aade48f5ea80651ed10add1506d3" alt="Warp Edit custom endpoint dialog with the Orq endpoint name, the v3 router URL, and two models added" width="1080" height="1108" data-path="images/gateway-warp-endpoint.png" />
</Frame>

Select a model from Warp's model picker. Requests now route through the **AI Gateway** and appear in [Traces](/docs/ai-studio/observability/traces).

<Warning>
  Always use the `provider/model_id` format for model names (e.g. `anthropic/claude-sonnet-5`, not `claude-sonnet-5`). Bare IDs return a `400 invalid model format` error.
</Warning>

### Troubleshooting

<AccordionGroup>
  <Accordion title="400 invalid model format">
    The model name is missing the provider prefix. Change `claude-sonnet-5` to `anthropic/claude-sonnet-5`, `gpt-5.6-sol` to `openai/gpt-5.6-sol`, and so on.
  </Accordion>

  <Accordion title="Requests not appearing in Orq.ai Traces">
    Verify the **Endpoint URL** is set to `https://my.orq.ai/v3/router`. Requests sent to a provider's own endpoint bypass the **AI Gateway** and produce no **Traces**.
  </Accordion>
</AccordionGroup>

## MCP

With the **Orq MCP** integration, access the **Orq.ai** workspace directly from Warp's AI features.

### Installation

1. Open Warp Settings by clicking **Warp** in the top-left menu, then select **Settings**
2. Click **MCP Server** in the sidebar
3. Click the **Add** button
4. Paste the following configuration:

```json wrap theme={"theme":{"light":"github-light","dark":"github-dark"}}
{
  "mcpServers": {
    "orq": {
      "url": "https://my.orq.ai/v2/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_ORQ_API_KEY"
      }
    }
  }
}
```

5. Replace `YOUR_ORQ_API_KEY` with your actual API key from [Workspace Settings → API Keys](https://my.orq.ai/settings/api-keys)
6. Save the configuration

The **Orq MCP** server should automatically connect. All Orq.ai tools will be available immediately.

### Verification

In Warp's AI features, 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 **Orq.ai** workspace will appear.

<Frame caption="Successfully connected Orq MCP in Warp">
  <img src="https://mintcdn.com/orqai/rjY3PTYrNubA6L2q/images/mcp-warp-success.png?fit=max&auto=format&n=rjY3PTYrNubA6L2q&q=85&s=c1c812fa235b31df2c450ca7b256ef2b" alt="Warp terminal showing the Orq MCP server connected and available in the AI features panel" width="2272" height="1760" data-path="images/mcp-warp-success.png" />
</Frame>

### Available Commands

Use natural language in Warp 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](/docs/ai-studio/integrations/code-assistants/orq-mcp) for the full tool reference and examples.

### Troubleshooting

<AccordionGroup>
  <Accordion title="Orq MCP Not Responding">
    1. Check Warp's **Orq MCP** status in Settings
    2. Verify the API key is correct
    3. Restart Warp
  </Accordion>

  <Accordion title="Authentication Errors">
    1. Confirm the API key is valid
    2. Ensure the API key has the necessary permissions
    3. Try regenerating the API key
  </Accordion>

  <Accordion title="Tools Not Available">
    1. Verify the **Orq MCP** server is running in Settings
    2. Check network connectivity
    3. Review Warp's own diagnostic output or [submit a bug report](https://docs.warp.dev/support-and-community/troubleshooting-and-support/sending-us-feedback/)
  </Accordion>
</AccordionGroup>

## Skills

**Orq Skills** add pre-built agentic workflows to Warp 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 warp
```

Set an [API key and connect the Orq MCP server](/docs/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="/docs/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>