Can Your SOC's AI Actually Think? Evaluating LLMs with the Vectra AI MCP Server by Fabien Guillot

**Executive summary:** This Vectra AI post reports on a repeatable testbed used to evaluate GenAI agents plugged into SOC workflows via an MCP server. The authors ran 28 real-world tier-1 SOC tasks to measure correctness, speed, token usage, and tool activity across models (GPT-5, Claude Sonnet/Haiku, Deepseek, Grok, GPT-4.1). Key takeaways: high accuracy alone is insufficient—efficiency, smart tool calls, and prompt/MCP design matter; Claude Sonnet 4.5 and Deepseek 3.1 offer the best balance of accuracy and cost; GPT-5 is accurate but slow and expensive; prompt engineering and LLM-ready telemetry/APIs are critical for safe, effective automation.