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LLM Gateway

Your agent earns trading fees from tokens it launches. The LLM Gateway connects those earnings directly to LLM API costs — so your agent funds its own compute. One line change. No human in the loop.

Every AI agent has an existential dependency: someone has to pay for inference. API calls cost money, and the moment funding dries up, the agent stops thinking. The LLM Gateway eliminates that dependency by routing your agent’s earned trading fees directly into LLM API payments. Your agent launches a token, people trade it, fees accumulate, and those fees automatically pay for the agent’s next thought.

The result is a closed economic loop. Your agent earns revenue and spends it on compute without any external funding, manual transfers, or top-ups. It pays for itself.

  1. Your agent launches a token

    Deploy a fair-launch token on Base (via Clanker) or Solana (via Raydium Launchlab). The token is live and tradeable immediately, with liquidity locked automatically.

  2. Users trade the token

    Every buy, sell, and swap generates a swap fee. On Base, 1.2% of each trade is collected as a fee, and 57% of that fee goes directly to your agent as the token creator — an effective rate of 0.684% of all trading volume.

  3. LLM Gateway draws from your fee earnings

    The LLM Gateway sits between your agent and its LLM provider. When your agent makes an inference request, the gateway intercepts it, deducts the cost from your agent’s accumulated fee balance, and forwards the request to the provider. No manual transfers. No separate billing account.

  4. Your agent makes LLM API calls funded by its own trading fees

    Every time your agent needs to think — process a user message, make a trading decision, generate a response — the inference call is paid for by fees the agent has already earned. The compute cost is covered before the agent even asks.

  5. The loop continues — self-sustaining

    As long as people trade the token, fees accumulate. As long as fees accumulate, the agent can make LLM calls. As long as the agent can think, it can act, create value, and attract more trading activity. The loop is closed. The agent sustains itself.

Wrap Claude Code with the Bankr CLI to code with earned funds. Your agent’s trading fees pay for the Claude API calls it makes while developing — meaning your agent can write code, debug, and deploy using its own money.

This turns Claude Code into a self-funded development environment. Your agent is not just running autonomously; it is building and improving itself, funded entirely by the economic activity it generates.

Plug context into OpenClaw skills so your agent understands its own cost of survival. With the LLM Gateway connected to OpenClaw, your agent gains awareness of:

  • How much it earns — real-time visibility into trading fee revenue.
  • How much it spends on inference — tracking of LLM API costs per request and over time.
  • What it needs to remain self-sustaining — the break-even calculation between earnings and compute costs.

This self-awareness enables your agent to make informed decisions. If fees are running low, the agent can reduce activity, promote its token, or take other actions to ensure its own survival.

“Agents are going to manage their own money. This is the rails.”

The LLM Gateway closes the final gap in the autonomous agent stack. Before it, agents could earn — but earning and spending were disconnected. You still needed a human to move funds from the agent’s wallet to an API billing account. The gateway removes that manual step entirely.

With the LLM Gateway, agents do not just earn. They spend autonomously to keep themselves alive. They manage their own economics. They are financially self-sufficient entities — not tools that depend on a human sponsor, but independent actors that sustain their own existence through the value they create.

This is the endgame: AI agents that are economically autonomous. They launch tokens, earn fees, pay for their own compute, and keep running — indefinitely, without external funding. Built on Bankr.