I built a tiny open-source way to prove what your AI agent actually did (offline, zero backend)

Reddit r/AI_Agents Tools
open-source cryptographic ai-agent verifiable-proof offline mit-license

Summary

ActionProof is an MIT-licensed library that generates tamper-evident cryptographic receipts for AI agent actions, enabling offline verification without backend infrastructure. It supports TypeScript, Python, and drops into Claude Desktop Cursor as an MCP server.

If you build agents that act (not just chat), you've probably hit this: after a run, how do you prove the agent really sent that email made that booking, and didn't just log that it did? Logs are self-asserted and forgeable. ActionProof is a small MIT library that makes each action a cryptographically signed, tamper-evident receipt — verify it later offline, no server, no account. Works in TypeScript and Python (receipts cross-verify), and drops into Claude Desktop Cursor as an MCP server so your agent emits receipts automatically. Genuinely want to know: is verifiable proof-of-action something you'd use, or do your existing logs observability already cover it? Trying to learn if this is a real gap.
Original Article

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AI agents are starting to do real work. But where’s the receipt?

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The article identifies a growing problem: AI agents can perform complex tasks, but their work is difficult to inspect, trust, and hand off. The author proposes a 'work receipt' system to provide transparent, shareable proof of what an agent did, including steps, sources, and confidence levels, aiming to help non-technical users confidently use agentic AI.