MPP - Machine Payments Protocol

Build with MPP (Machine Payments Protocol) - the open protocol for machine-to-machine payments over HTTP 402. Use when developing paid APIs, payment-gated co...

This skill appears to be a genuine MPP protocol SDK (server and client) and will require you to provide and manage sensitive secrets (mnemonics, private keys, server secret keys) and to handle on-chain deposits/refunds and long‑running transports. Before installing or using it: - Treat any examples that use MNEMONIC, private keys, or MPP_SECRET_KEY as instructions that will cause real funds to be spent if used against mainnet. Prefer testnet/regtest for evaluation. - The skill metadata does not declare required env vars; make sure you do not accidentally paste real private keys into a public environment. Use dedicated, minimal-permission wallets or ephemeral keys for testing. - Audit any third‑party packages it references (e.g., @buildonspark/lightning-mpp-sdk, mppx, stellar packages) before use. - Review where and how your app will persist secrets (.env, stores like Cloudflare KV/Redis) and ensure appropriate access controls and rotation policies. - Because session modes involve deposits and refunds, understand the escrow and close/recovery flows to avoid locked funds. If you want higher assurance: request the actual SDK package sources (npm/crates/pypi links & checksums), confirm which environment variables the integrator expects, and run the flows on a testnet/regtest environment first.

Type: OpenClaw Skill Name: mpp Version: 0.5.7 The "mpp" skill bundle is a comprehensive documentation and instruction set for the Machine Payments Protocol (MPP), an open standard for machine-to-machine payments using HTTP 402. It includes detailed SDK references for TypeScript (mppx), Python (pympp), and Rust (mpp), along with integration guides for payment rails like Tempo, Stripe, and Lightning. The SKILL.md file provides legitimate instructions for an AI agent to assist users in developing paid APIs and payment-gated services. No indicators of malicious intent, data exfiltration, or harmful prompt injection were found; the content is technically consistent and focused on its stated purpose of enabling automated payment flows.