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arXiv AI By Yitian Zheng, Zhaorun Chen, Haoyu Li, Bo Li

GatewayBench: Unified Capability and Security Evaluation Platform for MCP Gateways

Read the original on arXiv AI →

GatewayBench is a new evaluation framework that systematically studies how the design of Model Context Protocol (MCP) gateways influences AI agent capability, efficiency, and security. It categorizes gateways into flattened and hierarchical architectures and tests them on 524 tasks across six domains using a pool of 11,118 real-world tools from 251 MCP servers, including task-irrelevant tools to simulate large-scale deployments. Experiments on seven widely deployed gateways reveal significant differences in task completion, tool-use efficiency, and attack resilience, showing strong interactions with the underlying model and agent harness.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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