Integrate OpenClaw with CLōD to route your AI agent inference through CLōD’s OpenAI-compatible API endpoint.

This allows your OpenClaw agents to access multiple models through a single endpoint while using CLōD for unified model access and usage monitoring.

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What is OpenClaw?

OpenClaw is an open-source AI agent gateway that routes agent inference requests to configurable model providers.

By configuring CLōD as a provider, OpenClaw agents can send inference requests directly through the CLōD API.

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Setup

There are two ways to configure OpenClaw to use CLōD.

Recommended:
Use the OpenClaw onboarding wizard.

Advanced:
Manually configure the provider in the OpenClaw JSON configuration file.

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Recommended Setup (OpenClaw Onboard Wizard)

If you are setting up OpenClaw for the first time, the easiest method is using the built-in onboarding tool.

Run:

During onboarding select:

Provider: Custom Provider

Provider Name:

Base URL:

Note:
The /v1 suffix is required because CLōD uses an OpenAI-compatible API format.

You will also be prompted to enter your CLōD API key and configure your default model.

Once onboarding finishes, OpenClaw automatically creates the required configuration entries.

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Getting Your CLōD API Key

Before configuring OpenClaw you will need a CLōD API key.

1. Log in to the CLōD dashboard
2. Navigate to the API keys section
3. Generate a new API key

Dashboard:

https://app.clod.io

Copy the API key. You will use it in your OpenClaw configuration.

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Recommended Security Method (Environment Variable)

For better security, store your API key in an environment variable instead of placing it directly inside configuration files.

Example:

export CLOD_API_KEY="your_clod_api_key"

This keeps your API key out of version control and configuration files.

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Manual Configuration (Advanced)

Advanced users can configure CLōD directly in the OpenClaw configuration file.

Open:

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Add the CLōD provider configuration.

Example:

{
  "models": {
    "mode": "merge",
    "providers": {
      "custom-api-clod-io": {
        "baseUrl": "https://api.clod.io/v1",
        "apiKey": "YOUR_CLOD_API_KEY",
        "api": "openai-completions",
        "models": [
          {
            "id": "DeepSeek V3",
            "name": "DeepSeek V3 (CLŌD)",
            "reasoning": false,
            "input": ["text"],
            "contextWindow": 128000,
            "maxTokens": 4096
          }
        ]
      }
    }
  }
}

Replace:

YOUR_CLOD_API_KEY

with your actual CLōD API key.

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Using Environment Variables in JSON (Recommended)

Instead of placing the API key directly in the config file, you can reference the environment variable.

Example:

{
  "models": {
    "mode": "merge",
    "providers": {
      "custom-api-clod-io": {
        "baseUrl": "https://api.clod.io/v1",
        "apiKey": "$CLOD_API_KEY",
        "api": "openai-completions",
        "models": [
          {
            "id": "DeepSeek V3",
            "name": "DeepSeek V3 (CLŌD)",
            "reasoning": false,
            "input": ["text"],
            "contextWindow": 128000,
            "maxTokens": 4096
          }
        ]
      }
    }
  }
}

Then define the key:

export CLOD_API_KEY="your_clod_api_key"

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Choosing a Model

CLōD supports multiple models that can be used through OpenClaw.

Model identifiers should match the names listed in the CLōD model catalog.

Model catalog:

https://app.clod.io/user/models

Examples of available models:

• DeepSeek V3
• Llama 3.1 8B
• Minimax M2.5

When configuring a model in OpenClaw, use the exact name provided in the CLōD model list.

Example:

"id": "Llama 3.1 8B"

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Context Window Configuration

The contextWindow parameter must match the maximum context supported by the model you are using.

Typical values include:

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If you configure a context window larger than what the model supports, inference requests may fail.

Always verify supported context sizes on the CLōD model page.

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Starting OpenClaw

After configuration is complete, start or restart the OpenClaw gateway.

Example:

OpenClaw will load the custom-api-clod-io provider and route inference requests through CLōD.

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Monitoring Usage

Once OpenClaw is running with CLōD, you can monitor inference usage from the CLōD dashboard.

Dashboard:

https://app.clod.io

From the dashboard you can view:

• Request activity
• Token usage
• Model usage
• Total consumption

This helps track how your OpenClaw agents are using inference resources.