Run OpenClaw on BoostRail

A continuously running agent repeats context constantly. Where a model's route supports prompt caching, cached input bills at the cache-read price published for that model — at or below the provider's own cache-read price, DeepSeek V4 Pro, DeepSeek V4.1 Flash and Kimi K3 excepted — and cache writes carry no surcharge. Leading models are priced at or below their official list prices.

It also means a single provider outage or rate wall stops your agent mid-task. Through BoostRail you get one OpenAI-compatible endpoint across leading models, so switching models is a string change in your config rather than a new account, a new key, and a new integration.

{
  models: {
    mode: "merge",
    providers: {
      boostrail: {
        baseUrl: "https://api.boostrail.com/v1",
        apiKey: "${BOOSTRAIL_API_KEY}",
        api: "openai-completions",
        models: [
          {
            id: "claude-sonnet-5",
            name: "Claude Sonnet 5",
            input: ["text"],
            contextWindow: 200000,
            maxTokens: 64000,
          },
        ],
      },
    },
  },
  agents: {
    defaults: {
      model: { primary: "boostrail/claude-sonnet-5" },
    },
  },
}

• Set BOOSTRAIL_API_KEY in the environment OpenClaw runs in. The key value goes in the environment, not in the config file.
• Add one model entry per model you want to use, with the exact id from the Models page. The catalog ids are stable strings — claude-sonnet-5, deepseek-v4.1-flash, gpt-5.4, and so on.
• If your setup restricts models through agents.defaults.modelPolicy.allow, add the ref boostrail/* or the exact model refs — a provider definition alone does not make a model selectable.
• contextWindow and maxTokens describe the model you picked, not BoostRail. Check the Models page for the values that apply to your model, including the models that carry a context cap.

curl https://api.boostrail.com/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"claude-sonnet-5","messages":[{"role":"user","content":"reply with OK"}]}'

A working setup returns a JSON body with a choices array and the model's reply inside it. Your usage and the exact price applied to that request appear in the console within a few seconds.