AAAI 2026technical0 citations

MCP-AgentBench: Evaluating Real-World Language Agent Performance with MCP-Mediated Tools

Zikang Guo, Benfeng Xu, Chiwei Zhu, Wentao Hong, Xiaorui Wang, Zhendong Mao

Abstract

The Model Context Protocol (MCP) is rapidly emerging as a pivotal open standard, designed to enhance agent-tool integration and interoperability, and is positioned to unlock a new era of powerful, interconnected, and genuinely utilitarian agentic AI. However, despite MCP

BibTeX
@inproceedings{aaai2026_mcpagentbencheva,
  title = {MCP-AgentBench: Evaluating Real-World Language Agent Performance with MCP-Mediated Tools},
  author = {Zikang Guo and Benfeng Xu and Chiwei Zhu and Wentao Hong and Xiaorui Wang and Zhendong Mao},
  booktitle = {AAAI 2026},
  year = {2026}
}
MCP-AgentBench: Evaluating Real-World Language Agent Performance with MCP-Mediated Tools · AAAI 2026