# Zero-Knowledge Audit for Internet of Agents: Privacy-Preserving Communication Verification with Model Context Protocol

arXiv: https://arxiv.org/abs/2512.14737 · HTML: https://mlsanity.com/paper/2512.14737/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Placed in Agent threats, guardrails and governance, one of 16 directions in LLM agents and tool use.
- Builds on 6 of its 28 references that are in the map.
- First posted on arXiv 11 Dec 2025.

## Placed in

- LLM agents and tool use / [Agent threats, guardrails and governance](https://mlsanity.com/agents/agent-threats-guardrails-and-governance/)

## Builds on (most cited first, 6 of 6)

- [Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions](https://mlsanity.com/paper/2503.23278/) (2025)
- [LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models](https://mlsanity.com/paper/2309.12307/) (2023)
- [Enterprise-Grade Security for the Model Context Protocol (MCP): Frameworks and Mitigation Strategies](https://mlsanity.com/paper/2504.08623/) (2025)
- [Advancing Multi-Agent Systems Through Model Context Protocol: Architecture, Implementation, and Applications](https://mlsanity.com/paper/2504.21030/) (2025)
- [A Survey on the Applications of Zero-Knowledge Proofs](https://mlsanity.com/paper/2408.00243/) (2024)
- [Distributed Non-Interactive Zero-Knowledge Proofs](https://mlsanity.com/paper/2502.07594/) (2025)

## Built on by (most cited first, 1 of 1)

- [Cryptographically verifiable authorization for autonomous AI agents: a falsifiable hypothesis and proof of concept](https://mlsanity.com/paper/2607.21325/) (2026)

## Abstract (arXiv)

Existing agent communication frameworks face critical limitations in providing verifiable audit trails without compromising the privacy and confidentiality of agent interactions. The protection of agent communication privacy while ensuring auditability emerges as a fundamental challenge for applications requiring accurate billing, compliance verification, and accountability in regulated environments. We introduce a framework for auditing agent communications that keeps messages private while still checking they follow expected rules. It pairs zero-knowledge proofs with the existing Model Context Protocol (MCP) so messages can be verified without revealing their contents. The approach runs in lightweight networks, stays compatible with standard MCP exchanges, and adds asynchronous audit verification to confirm format and general message types without exposing specifics. The framework enables mutual audits between agents: one side can check communication content and quality while the other verifies usage metrics, all without revealing sensitive information. We formalize security goals and show that zk-MCP provides data authenticity and communication privacy, achieving efficient verification with negligible latency overhead. We fully implement the framework, including Circom-based zero-knowledge proof generation and an audit protocol integrated with MCP's bidirectional channel, and, to our knowledge, this is the first privacy-preserving audit system for agent communications that offers verifiable mutual auditing without exposing message content or compromising agent privacy.