Tool-Calling LLM Agents Under Realistic MCP Faults: Scale Does Not Purchase Fault Tolerance

The paper introduces MCP‑Injector, a fault‑injection middleware that simulates realistic failures in the Model Context Protocol used by large‑language‑model agents. Using data from over 57,000 issue and pull‑request threads, the authors calibrate a fault model and run 1,350 experiments across different backbone sizes, agent stacks, and fault conditions. Results show that permanent‑heavy faults drastically reduce task‑completion scores and that larger models (120B) do not gain fault tolerance, highlighting that framework‑level error handling is more critical than model scale.

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• llms
• agents
• benchmarks