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szhygulin/recon-crypto-mcp

by Various

Safety first. Hardware-verified DeFi for AI agents — designed for when the AI can be compromised.

S

MCP

szhygulin/recon-crypto-mcp

Added 1 June 2026

#aave #ai-agent #arbitrum #claude #claude-code #compound #crypto #cursor

Overview

A TypeScript-based Model Context Protocol (MCP) server that enables AI agents to interact with DeFi protocols using hardware-level verification. It ensures transactions remain safe even when the AI agent is compromised by requiring cryptographic proof from a trusted hardware component.

Best for

Best for
Developers building AI agents that execute DeFi operations and prioritize security against agent compromise

Use cases

  • Secure DeFi transaction execution by AI agents
  • Prevent unauthorized token transfers from compromised agents
  • Add hardware-backed cryptographic verification to agent-based DeFi workflows

How to use

Install

npx -y vaultpilot-mcp

Tested with

Claude Code, Cursor, Claude Desktop

Notes

A TypeScript-based Model Context Protocol (MCP) server that enables AI agents to interact with DeFi protocols using hardware-level verification. It ensures transactions remain safe even when the AI agent is compromised by requiring cryptographic proof from a trusted hardware component.

3 stars on GitHub. Last updated 2026-05-26.

Use cases

  • Secure DeFi transaction execution by AI agents
  • Prevent unauthorized token transfers from compromised agents
  • Add hardware-backed cryptographic verification to agent-based DeFi workflows

Pros

  • Provides a hardware-rooted trust layer for AI-driven DeFi operations
  • Mitigates risks of compromised AI agents
  • Open-source TypeScript implementation for easy integration

Cons

  • Requires compatible hardware (e.g., TEE or HSM) which adds deployment complexity
  • Limited community adoption and few real-world deployments
  • Narrow focus on DeFi may restrict use beyond crypto transactions

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Provides a hardware-rooted trust layer for AI-driven DeFi operations
  • Mitigates risks of compromised AI agents
  • Open-source TypeScript implementation for easy integration

Cons

  • Requires compatible hardware (e.g., TEE or HSM) which adds deployment complexity
  • Limited community adoption and few real-world deployments
  • Narrow focus on DeFi may restrict use beyond crypto transactions
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