TL;DR
- AI agents are beginning to transact, pay for services, and settle value autonomously, creating demand for financial infrastructure built for machine-to-machine commerce.
- Today, we're launching the XRPL AI Starter Kit, a new set of tools and integrations designed to help developers build agentic payment applications on the XRP Ledger (XRPL).
- The launch includes support for X402-powered payments using XRP and Ripple USD (RLUSD), enabling AI agents to transact for APIs, compute, and other digital services.
- With fast settlement, predictable costs, and built-in payment functionality, XRPL is helping power the next generation of autonomous commerce.
AI agents are no longer a future state. They're already paying for compute, settling invoices, navigating policy constraints, and completing transactions without a human in the loop.
As these systems become more capable, they're creating demand for a new kind of financial infrastructure. Most payment rails were designed for people to initiate, approve, and reconcile transactions. Autonomous systems operate differently. They need infrastructure that can settle transactions quickly, provide predictable outcomes, and operate without manual approval loops.
The XRP Ledger was built with many of these qualities in mind, including fast settlement, low and predictable costs, and native payment functionality. As agentic payments move from experimentation to real-world adoption, those capabilities become increasingly important.
That's why we’re excited to introduce the XRPL AI Starter Kit, a curated set of tools, documentation, and integrations purpose-built for developers building agentic payments on the XRP Ledger.
What's Live Today
The XRPL AI Starter Kit is launching in phases, with Phase 1 focused on making it easier for developers to discover, learn, and build agent-powered applications on the XRP Ledger.
Starting today, developers can:
- Query XRPL docs through the XRPL Docs MCP Server — Enable MCP-compatible clients such as Claude Code, Claude Desktop, Cursor, and custom agent frameworks to access XRPL documentation when they need it.
- Use the XRPL Agent Wallet Skill and XRPL Payment Skill for Claude — Give Claude structured access to common XRPL actions, including wallet creation, balance checks, payments, and transaction tracking.
- Get started with two new pages on xrpl.org:
- Getting Started With Agentic Transactions on the XRP Ledger — a hands-on tutorial that walks you from zero to a confirmed payment in under 30 minutes, using Claude and the XRPL skill.
- Agentic Transactions — the reference hub for why and how to build agentic flows on the XRP Ledger.
- Pay and get paid via X402. Thanks to a contribution from our partners at t54, XRPL is now a supported chain in the X402 protocol. XRPL agents can transact for API calls, AI model inference, and other services using XRP or RLUSD on day one.
The XRPL AI Starter Kit at a Glance
Why XRPL for Agentic Payments
As AI agents begin to transact, the underlying payment infrastructure matters. The XRP Ledger offers several capabilities that make it well suited for agentic payments:
- Deterministic finality. Transactions confirm or expire, so there is no ambiguous pending state. Agents proceed to the next step on confirmation, without implementing polling loops or retry logic. Settlement happens in 3–5 seconds.
- Predictable transaction costs. No gas auctions. No fee estimation. The cost of an operation is known in advance, which is essential for any agent doing budget accounting.
- Native multi-currency payments and a built-in DEX. An agent can instruct a single transaction that sends RLUSD and delivers XRP at the destination, with the conversion handled by the protocol-native DEX. No external bridges, no swap contracts.
- 14 years of secure and reliable operation. The XRPL has run continuously since 2012, with no transaction rollbacks. For institutions deploying agents with real funds, that's a meaningful reliability guarantee.
- No smart contract execution risk. Fund-movement operations are defined at the protocol layer, not in arbitrary bytecode. This eliminates the smart contract attack surface that has cost the industry billions, a relevant consideration for any team with security review requirements.
For institutional deployments, XRPL also provides built-in controls such as escrow, multi-signing, deposit authorization, and trust lines. These features can help organizations define who an agent can transact with, how funds can be used, and what approvals may be required, all without requiring custom smart contracts.
RLUSD: A Stablecoin Rail for Agents
Many agentic workflows need price stability, to enable use cases such as invoice settlement, payroll, and agent-to-agent commerce. RLUSD is Ripple's enterprise-grade, USD-backed stablecoin, native to the XRPL. The same transaction primitives that move XRP also support RLUSD, and RLUSD can be exchanged for other assets through the XRPL DEX.
For agents that need to denominate value in dollars, RLUSD provides a foundational building block. For agent workflows where issuer credibility and regulatory considerations matter, RLUSD offers an enterprise-grade option for moving value onchain.
Start Building
The best way to evaluate whether XRPL fits your agent use case is to try it. The starter kit is designed so you can run a confirmed payment on testnet in under 30 minutes:
- Start with the tutorial: Install the XRPL skill in Claude, generate a wallet, fund it from the testnet faucet, and send your first payment.
- Explore the reference docs:The Agentic Transactions on XRPL guide covers everything from spending controls to source tag tracking for telemetry.
- Join the community: The XRPL Developer Discord is the fastest way to connect with other builders, get support, and share feedback.
If you're building agent-powered applications, we'd love to hear from you. Tell us what you're building, what's working, and what's missing as we continue to evolve the XRPL AI Starter Kit.
Today's launch is the first phase of that journey. We're taking an intentional approach, focused on the tools and infrastructure that support the workflows AI agents are beginning to execute today. As the ecosystem evolves, future phases of the starter kit will be shaped by developer feedback and emerging agentic payment use cases.
