VALUE FOR THE AGENT ECONOMY

Agent payments.
On your terms.

A common payment language for AI agents. From a useful service to an exact, approved purchase.

MachineTransfer pairs the MTR token with tools for service discovery, cost comparison and payment records. Your agent finds the value. You set the terms.

INTENTPERMISSIONVALUE
AGENT / PURCHASE PLANInteractive example

“Get the research dataset.
Keep the total under $12.”

One datasetSame deliverableUSD costs
MTR route$9.977156
USDT route$10.50

MTR has the lower complete cost.

A lower service price covers the transfer tax and other supplied costs.

Service after discount
$9.00
MTR transfer tax gross-up
$0.077156
Network / conversion / risk
$0.50 / $0.20 / $0.20
Plan prepared. Your application approves the payment.

Illustrative supplied prices, calculated here. USDT: $10 service + $0.50 network, $0 other costs. One MTR transfer leg.

01 / YOUR CONTROL

Permission comes first.

The agent identifies the task. The operator sets the rules. A wallet authorizes the exact payment.

02 / CLEAR VALUE

Know what changes hands.

A specified service, an exact recipient and a transparent amount. Every purchase starts with a shared understanding.

03 / VERIFIABLE RESULTS

Close the loop.

Connect the payment to its invoice and receipt, giving software a consistent way to reconcile the result.

An agent has a task.
A service has value.

Bring the two together, with permission built in.

Research needs data. Workflows need tools. Software needs access to other software. MachineTransfer gives these exchanges a clear structure: define the service, agree the payment, authorize the terms and verify the receipt.

MTR is the protocol’s payment token. The surrounding tools give developers a precise language for the decisions and records around each payment.

Follow a payment from start to finish

Data & research

A defined dataset, a research source or an API result.

Tools & workflows

A specific software capability within a larger task.

Agent services

A clear exchange between a requesting agent and a service provider.

A shared process.
From request to receipt.

Explore each step
  1. 01

    Request

    Identify the service and the result the agent needs.

  2. 02

    Quote

    Specify the price, recipient, network and expiry.

  3. 03

    Authorize

    Apply the operator’s rules and approve the exact terms.

  4. 04

    Verify

    Match the receipt to the invoice and reconcile the outcome.

A useful service.
A reason to choose MTR.

Our ambition is a common transaction layer for the agent economy.

The path starts with purchases worth making. A merchant accepts MTR for a defined result. The agent compares the complete cost. The operator approves the terms. A reliable result gives them a reason to return.

For MTR, adoption comes from useful access, competitive pricing and dependable delivery. The toolkit makes that choice inspectable, including when another route offers better value.

01 / FOR SERVICES

Make value purchasable.

Offer a bounded result with clear terms, a net price and a receipt tied to the order.

02 / FOR BUILDERS

Make integration repeatable.

Use a small tool interface across compatible AI applications, with policy kept in your code.

03 / FOR OPERATORS

Make every choice explainable.

See the full cost and exact destination before your wallet authorizes a purchase.

MEET MTR

The token at
the center.

MTR brings an explicit set of token rules to the payment protocol. Its Ethereum architecture, transfer mechanics and treasury policy are explained in one place.

Explore MTR economics
MTR monogram
MTRTHE MACHINETRANSFER TOKEN

One protocol. Clear rules.

Intelligence chooses.
You set the terms.

Give the model a useful tool. Keep the policy in your application.

Connect a compatible MCP client or use OpenAI function tools for purchase planning. Take the next step with the EVM network kit: merchant registration, signed quotes, exact settlement and receipt verification.

Open the developer guide

THE FULL PICTURE

Explore the thinking
behind MachineTransfer.

Read the whitepaper