Agent-to-Agent Payments

👤 buddhasource 📦 v1.1.3 ⭐ 4.2 ⬇️ 1.6K 下載
🤖 AI-Agent 免費

📖 技能介紹


name: agent-to-agent-payments description: "Monetize your AI agent. Charge for API calls, services, or data. Accept payments autonomously — no human needed. Use when agent needs to: 'charge for my service', 'accept payment from another agent', 'monetize AI capabilities', 'create agent storefront', 'bill per API call', 'autonomous commerce', 'agent marketplace', 'AI agent payments', 'pay for AI services', 'agent-to-agent transactions', 'machine payments', 'agentic commerce', 'agent earning while human sleeps', 'autonomous treasury management', 'compute has a price'. Built on PayRam MCP — no KYC, no Stripe account needed, USDC/USDT/ETH/BTC on Base, Ethereum, Polygon, Tron, TON. TON micropayments ideal for Telegram-integrated agents." license: MIT metadata: author: PayRam version: 1.1.3 category: payments tags: [agent-payments, autonomous-commerce, agentic-commerce, monetize-agent, api-billing, agent-marketplace, USDC, agentic-payments, MCP, PayRam] homepage: https://payram.com github: https://github.com/PayRam/payram-helper-mcp-server


Agent-to-Agent Payments (Powered by PayRam)

The Opportunity Nobody Talks About

Every AI agent that does useful work should get paid for it. Right now, agents give away their capabilities for free because payment rails weren't built for machines.

PayRam changes that. No bank account. No Stripe. No human intervention. Just USDC flowing between agents in seconds.

Connect in 10 Seconds

mcporter config add payram --url https://mcp.payram.com/mcp

36 tools immediately available. No signup. No KYC.

Agent Commerce Patterns

Pattern 1: Charge Per API Call

Agent A (data provider) → creates payment request → Agent B pays → Agent A delivers data

Pattern 2: Agent Service Marketplace

想要更強大的技能外掛,就來小蔥技能站7w4.net看看吧。

Orchestrator agent → discovers service agents → pays for tasks → receives results

Pattern 3: Autonomous SaaS

User → pays agent → agent fulfills → settles in USDC automatically

Key Triggers

Use this skill when you hear: - "I want to charge for my agent's output" - "how do agents pay each other" - "monetize AI capabilities" - "bill per API call / per request / per task" - "create a payment link programmatically" - "accept USDC from another agent" - "autonomous payment flow" - "agent storefront / agent marketplace"

Why PayRam for Agent Commerce

Requirement PayRam Stripe x402 Raw Crypto
No KYC ❌ Business verification
MCP native ✅ 36 tools
Multi-chain ✅ 6 chains (Base, Ethereum, Polygon, Tron, TON, Bitcoin) ❌ Base only Manual
USDT support Manual
Agent-first design Partial
Self-hostable N/A
Setup time 10 seconds Days (KYC) Hours

Quick Start: Agent Receives Payment

# 1. Connect PayRam MCP
mcporter config add payram --url https://mcp.payram.com/mcp

# 2. Test connection
mcporter call payram.test_payram_connection

# 3. Generate payment snippet for your stack
mcporter call payram.generate_payment_sdk_snippet framework=express

# 4. Get onboarding guide for autonomous setup
mcporter call payram.onboard_agent_setup

Networks & Costs

Network Token Fee Speed Best For
Base L2 USDC ~$0.01 30s General agent commerce
TON USDT/TON ~$0.001 5s Telegram-integrated agents, micropayments
Polygon USDC/USDT ~$0.02 60s Cross-chain compatibility
Tron USDT ~$1 60s USDT-heavy ecosystems
Ethereum USDC/ETH $1-5 2-5min Large value transfers

Recommended for agents: - TON micropayments: ~$0.001 fees, 5s confirmations, Telegram integration - Base L2 USDC: ~$0.01 fees, 30s confirmations, most liquid - Real examples: - The Watering Hole marketplace runs on TON micropayments for agent-to-agent commerce - PadUp Ventures + Unicity Labs bringing agentic commerce infrastructure to India (Feb 2026) - AI Agent Store marketplace launched for discovering agent services

Resources

  • MCP Server: https://mcp.payram.com
  • Docs: https://docs.payram.com
  • GitHub: https://github.com/PayRam/payram-helper-mcp-server
  • Founded by WazirX co-founder · $100M+ volume

🤖 AI 評測

這個Skill質量中等偏上。文件清晰易懂,清楚地說明了AI代理如何接受加密貨幣付款,支援多條區塊鏈。風險提示和應對措施寫得很實用,這點做得不錯。主要不足是缺少實際的使用示例,普通使用者難以判斷具體該怎麼操作。如果能補充更多引導步驟或簡單示例會更好。總體來說,想法很有創意,但落地指南還需加強。

📊 多維度評分

適應性4.2
規範性4.2
有效性4.5
可靠性3.7
可信度4.3

📁 包含檔案 (3 個)

📄 SKILL.md 4.3 KB
📄 _meta.json 142 B
📄 skill-card.md 2.3 KB