MCPEvol-Bench: Benchmarking LLM Agent Performance Across Dynamic Evolutions of MCP Servers

TL;DR - MCPEvol-Bench is a new benchmark that evaluates how well LLM agents adapt when Model Context Protocol (MCP) server tools evolve over time, a dimension existing tool-use benchmarks ignore. It matters because it exposes how brittle even frontier agents are when tool interfaces change in production.

• Introduces 11 mutation operators (informed by an empirical study) to simulate realistic tool evolution across 123 MCP servers, testing agents on multiple server versions.
• Benchmarks 12 state-of-the-art LLMs; even frontier models struggle to adapt to evolving toolsets.
• Reports performance declines of 13.7% (GPT-5.4) and 14.4% (Claude-Sonnet-4-6) on evolved servers, with notable rises in planning and reasoning errors.
• Positions the benchmark as a standard for assessing agent adaptability in dynamic tool environments, highlighting vulnerability of LLM-driven workflows.