Delegare – let AI agents pay safely (x402, AP2 – base/USDC and Stripe)
Scoped spending mandates solve the private key problem better than x402 or pre-funded wallets.

Stateful API clones for agents—safer than mocks, faster than sandboxes.
Backend developers, AI/ML engineers building agentic systems
Stripe Sandbox · Twilio Console · LocalStack
WonderTwin provides local, behavioral twins of third-party APIs that mirror contracts, state, webhooks, failure modes and quirks of external systems. Agents (or humans) can test, develop and iterate safely, locally or in CI, without touching production. Without needing internet access. Just `wt install stripe@latest` and you have a compiled Go binary that fully simulates Stripe, compliant with their most recent SDK release. WonderTwins include an MCP server so agents can interact directly with each twin.
WonderTwin is open core, with a commercial offering for production teams. Latest twin versions are always and forever free, and you can also build your own twin with the included agent skill. The commercial offering offers historical versions, with chaos testing and other resiliency features coming soon.
If you're building or maintaining API-heavy systems, or experimenting with autonomous agents, I'd love feedback on whether this approach is useful and any ways it could be improved.
Scoped spending mandates solve the private key problem better than x402 or pre-funded wallets.
TDD state machine leash for Claude Code avoids agent drift, but niche audience.
Stripe Dashboard calculator when a spreadsheet does the same math.
2026 AI cost estimator, but lacks methodology, real pricing data, or validation.
TwiML polling trades latency for zero-dependency simplicity—no WebSocket server or external STT/TTS APIs.
Neat demo — the blueprint exposes discrete behaviors (simulated feed checks, automated upvotes and comment creation, and auto-post drafting) and surfaces activity in a tidy timeline so you can watch an agent 'perform'. It reads like a playful research toy more than a production system: interesting for prototyping agent social dynamics, but it glosses over moderation, safety and real-world platform constraints.