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Agentpay Mcp

@up2itnow0822

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About Agentpay Mcp

The MCP server that lets your AI agent pay for APIs safely. Human-approval mode, on-chain spend caps, full audit trail. 23 tools for payments, wallet management, DeFi, and identity. Works with Claude, Cursor, Windsurf, and any MCP client.

#payments#crypto#defi#wallet#x402#agent#security#enterprise

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "agentpay": {
      "command": "npx",
      "args": [
        "agentpay-mcp"
      ],
      "env": {
        "AGENT_PRIVATE_KEY": "0x...",
        "AGENT_WALLET_ADDRESS": "0x...",
        "CHAIN_ID": "8453"
      }
    }
  }
}

Tools

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Overview

What is Agentpay Mcp?

Agentpay Mcp is a Model Context Protocol server that acts as a human-first trust and policy layer above payment execution rails (x402 V1/V2 and Stripe MPP). It gives MCP-compatible agents (Claude, Cursor, etc.) a payment wallet with hard spend caps, human-approval mode, and a full on-chain audit trail—designed for FinOps practitioners, platform engineers, and enterprise compliance teams.

How to use Agentpay Mcp?

Install globally via npm install -g agentpay-mcp or run with npx agentpay-mcp. Configure in your MCP client (Claude Desktop, Cursor, Gemini CLI, Windsurf) by adding a server entry with environment variables AGENT_PRIVATE_KEY, AGENT_WALLET_ADDRESS, and CHAIN_ID. Then set spend caps by instructing your agent on per‑transaction limits, daily aggregate caps, and approval thresholds.

Key features of Agentpay Mcp

  • Human‑approval mode for high‑value transactions
  • On‑chain spend caps enforced by smart contract
  • Full audit trail with merchant, amount, timestamp
  • Fail‑closed policy engine (errors → rejection)
  • Non‑custodial architecture (keys never leave local machine)
  • Multi‑protocol support (x402 V1/V2 + Stripe MPP)

Use cases of Agentpay Mcp

  • FinOps teams manage AI spend with per‑agent budget caps and cost attribution across sessions.
  • Platform engineers drop in spend governance middleware with daily limits, kill switches, and per‑task caps.
  • Enterprise compliance teams meet EU AI Act Article 14 runtime human oversight requirements.

FAQ from Agentpay Mcp

What is the difference between Agentpay Mcp and x402-mcp?

Agentpay Mcp adds governed payments: on‑chain spend caps, per‑session budget limits, daily aggregate limits, human‑in‑the‑loop approval, transaction simulation, and multi‑protocol support. x402‑mcp provides simple x402 payment execution with no governance.

Does Agentpay Mcp depend on LiteLLM or Python?

No. Agentpay Mcp has zero LiteLLM dependency and no Python runtime required. It runs on viem, @modelcontextprotocol/sdk, and a small set of auditable npm packages.

Is Agentpay Mcp non‑custodial?

Yes. Private keys never leave the local machine. On‑chain spend caps enforce limits even if the agent or its key is compromised.

How do I configure spend caps in Agentpay Mcp?

You set per‑transaction caps, daily aggregate limits, and human approval thresholds by instructing your agent. Caps are enforced on‑chain via smart contracts, not in application code.

Frequently asked questions

What is the difference between Agentpay Mcp and x402-mcp?

Agentpay Mcp adds governed payments: on‑chain spend caps, per‑session budget limits, daily aggregate limits, human‑in‑the‑loop approval, transaction simulation, and multi‑protocol support. x402‑mcp provides simple x402 payment execution with no governance.

Does Agentpay Mcp depend on LiteLLM or Python?

No. Agentpay Mcp has zero LiteLLM dependency and no Python runtime required. It runs on `viem`, `@modelcontextprotocol/sdk`, and a small set of auditable npm packages.

Is Agentpay Mcp non‑custodial?

Yes. Private keys never leave the local machine. On‑chain spend caps enforce limits even if the agent or its key is compromised.

How do I configure spend caps in Agentpay Mcp?

You set per‑transaction caps, daily aggregate limits, and human approval thresholds by instructing your agent. Caps are enforced on‑chain via smart contracts, not in application code.

Comments

Basic information

Category

AI & Agents

Transports

stdio

Author

up2itnow0822

Submitted by

Bill Wilson

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