Governs AI agents' spending by enforcing budgets, approvals, and kill switches before any payment, providing an MCP interface for tool calls with policy checks.
A policy enforcement, audit, and evaluation control plane for LLM agents on payment infrastructure, intercepting tool calls at the MCP boundary to classify, redact, and allow/deny/escalate actions before execution.
Enables AI agents to evaluate every payment intent against user-signed, on-chain-anchored policies before money moves, returning allow, deny, or human-approval verdicts. Provides policy versioning, revocation, spend reports, and audit trails through MCP tools that agents cannot alter without the owner's key.
Deterministic, auditable payment policy enforcement for AI agents. It provides pre-action authorization with scopes, budgets, allowlists, and signed mandates via an MCP server.
Enables AI agents and MCP clients to route every tool call through configurable rules that allow, block, or hold risky actions for human approval, while recording decisions in a tamper-evident audit trail.