Insights on API economics, agent governance, and the future of machine-to-machine commerce.
Free tools
Use these calculators to put numbers on AI agent spend risk and grade your setup.
Estimate ghost spend, annual exposure and payback.
Model loop, retry, fanout, and paid tool-call exposure.
Route Cursor or Claude Code through SatGate with the snippet from MCP Setup.
Score identity, budgets, MCP tools, revocation, routing, and signed receipt proof.
Learn how spending controls for AI agents work before the request goes through.
Satya Nadella says to treat AI models as insider risks and keep the controls outside the model. What that asks of agent builders, and what SatGate does today.
Microsoft Scout shows where enterprise agents are headed: identity and access matter, but external agent actions also need economic authority, payment ownership, and proof.
Usage-based AI pricing makes cost an operating risk. Learn why enterprises need controls before the request goes through to observe, control, and prove AI agent spend.
Learn how to set up a Cursor MCP proxy with SatGate to enforce budgets, meter tool usage, and add signed receipts without changing your MCP servers.
Stop guessing tool costs on day one. Start everything at 1 credit in Observe mode, measure real usage, then use that data to shape behavior with intentional pricing.
Learn how to enforce OpenAI API budget limits before each request, then use the ROI calculator to quantify avoided agent-loop spend.
Zero Trust for AI agents needs scoped capability tokens, revocation, delegation limits, and budget enforcement before the request goes through.
HTTP 402 Payment Required has been "reserved for future use" since 1997. AI agents finally make it essential. Here are the real-world use cases unlocking it.
L402 combines HTTP 402 Payment Required with Lightning Network micropayments and macaroon tokens. Learn how this protocol enables AI agents to pay for API access in real time.
API keys tie identity to unlimited access. Macaroon tokens embed capabilities and constraints. For AI agents that need delegation and budget limits, the difference is everything.
InformationWeek's 9 recommendations for AI agent cost control are solid for 2025. But when agents make hundreds of calls per task and run around the clock, process can't keep pace. 7 of 9 are automatable at the infrastructure layer.
Monetize APIs for AI agents with machine-readable pricing, metering before the request goes through, budget enforcement, and charging external agents.
A complete MCP gateway guide covering architecture, auth, tool aggregation, and the spending controls most guides miss. Deploy with budget enforcement.
Economic firewalls protect against runaway AI agent costs — but what happens when attackers deliberately try to exploit them? We examine four adversarial attack vectors and the cryptographic defenses that stop them.
Observe, Control, Prove is an enterprise change management strategy for adopting spending controls incrementally, building trust at each stage.
Why autonomous AI agents need rules and receipts for AI agents: hard spend ceilings, bounded authority, revocation, signed receipts, and enforcement before the request goes through.
API teams need AI governance that enforces budgets, permissions, and signed receipts — not just traffic routing. Learn why traditional API management falls short.
LLM cost dashboards show what happened. Real-time enforcement controls what agents can spend before the bill arrives.
AI agent gateways need budget enforcement, MCP tool cost control, scoped tokens, revocation, and L402 beyond routing.
DeepMind's Intelligent AI Delegation points to macaroon capability tokens and delegation controls before the request goes through.
Set AI agent spending limits with hard budgets per agent, tool and route, and daily or weekly dollar limits on trade orders.
Control AI agent API costs with budget checks before the request goes through, tool pricing, delegated spend limits, revocation, and rules and receipts for AI agents.
An economic firewall enforces budget limits on AI agent API calls at the gateway layer. Learn how it differs from traditional API security and why agents need it.
Set per-tool MCP costs, cap agent spend, delegate budgets, and block runaway MCP tool calls before execution.
Control agent swarm costs with hierarchical budgets, scoped delegation tokens, cascade revocation, and enforcement before the request goes through.
Here's the CFO math on why spending controls pay for themselves.
Hard-cap MCP tool spend for Claude Code, Cursor, and agent loops with budget enforcement before the request goes through.
2,164 lines of Go, 28 tests, and one evening. An open-source MCP proxy that enforces per-tool budgets with cryptographic delegation.
The MCP ecosystem talks about capability. Nobody talks about cost. Here's why economic policy is the missing layer — and how to enforce it at the protocol level with L402 and macaroons.
AI gateways excel at routing LLM calls. But when agents control spend autonomously, routing isn't enough. You need spending controls.
FAQ
The SatGate blog covers AI agent governance, rules and receipts for AI agents, AI agent cost control, MCP budget enforcement, revocable capability tokens, charging external agents, and API economics for autonomous agents.
Start with the AI agent cost control guide, the economic firewall definition, the ROI calculator, and the MCP budget enforcement guide to understand the controls needed before the request goes through, before agents spend.
LLM dashboards report spend after it happens and traditional API gateways mainly route traffic. SatGate checks each request before it goes through, to observe, control, and prove agent/API activity at the gateway before forwarding.