Guardrails for AI agent payments.
Attribute every paid API call, tool purchase, and protocol payment to the agent, tool, and session that made it. Set budgets, enforce approvals before settlement, and reconcile the result — without holding your funds or private keys.
Spend Control stops AI agents from overspending by attributing every paid API call to an agent, tool, and session, then checking it against your budgets and approval rules before the money moves — and reconciling the result afterwards, without ever holding your funds or keys.
Autonomous agents spend real money — often with no one watching.
A single misconfigured agent can issue thousands of paid API calls without a human in the loop. Spend Control makes that spend visible and bounded before it becomes a bill. Read how on the blog →
Attribute
Know which agent, tool, and session initiated every paid call.
Control
Apply budgets, allowlists, and approval rules before money moves.
Reconcile
Verify settlement independently and export a defensible audit trail.
Practical guides to agent spend, payments, and audit.
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@harpd/observe
Zero-dependency transaction observability for AI agents.
agent-budget-policy
Declarative budgets and approval rules for agent payments.
x402-logging-middleware
Request/response logging for x402 payment flows.
agent-transaction-audit-schema
A portable schema for agent transaction audit trails.
mcp-paid-tool-starter
Starter kit for paid MCP tools and per-call billing.
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These products stand on their own for specific workflows. Spend Control is our platform bet; Labs are live experiments we keep honest.
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