# AI evals for MCP in AIOps

DevFeed: [AI evals for MCP in AIOps](<https://devfeed.tech/articles/ai-evals-for-mcp-in-aiops-57176.md>)

Original publisher: [Read original article](<https://www.thoughtworks.com/insights/blog/generative-ai/AI-evals-for-MCP-in-AIOps>)

Author: Zichuan Xiong, Larissa Dornelles, Scott Juang

Published: 2025-07-31T00:00:00Z

Content type: article

Language: en

Sources: [Thoughtworks Insights](<https://devfeed.tech/sources/thoughtworks-insights.md>)

Topics: [Model Context Protocol](<https://devfeed.tech/topics/model-context-protocol.md>), [AIOps](<https://devfeed.tech/topics/aiops.md>), [agentic workflows](<https://devfeed.tech/topics/agentic-workflows.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Context-aware AI](<https://devfeed.tech/topics/context-aware-ai.md>), [Risk](<https://devfeed.tech/topics/risk.md>), [telemetry](<https://devfeed.tech/topics/telemetry.md>), [Security](<https://devfeed.tech/topics/security.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [Authorization](<https://devfeed.tech/topics/authorization.md>), [Availability](<https://devfeed.tech/topics/availability.md>)

Tags: [agentic-workflows](<https://devfeed.tech/tags/agentic-workflows.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [ai-and-ml](<https://devfeed.tech/tags/ai-and-ml.md>), [ai-evals](<https://devfeed.tech/tags/ai-evals.md>), [aiops](<https://devfeed.tech/tags/aiops.md>), [availability](<https://devfeed.tech/tags/availability.md>), [blog](<https://devfeed.tech/tags/blog.md>), [compliance](<https://devfeed.tech/tags/compliance.md>), [context-aware-ai](<https://devfeed.tech/tags/context-aware-ai.md>), [decision-making](<https://devfeed.tech/tags/decision-making.md>), [distributed](<https://devfeed.tech/tags/distributed.md>), [evaluations](<https://devfeed.tech/tags/evaluations.md>), [generative-ai](<https://devfeed.tech/tags/generative-ai.md>), [hallucinations](<https://devfeed.tech/tags/hallucinations.md>), [latency](<https://devfeed.tech/tags/latency.md>), [mcp](<https://devfeed.tech/tags/mcp.md>), [permissions](<https://devfeed.tech/tags/permissions.md>), [security](<https://devfeed.tech/tags/security.md>)

## AI overview

This article examines how AI evaluations can be embedded into MCP-driven AIOps workflows. It describes how context-aware agents retrieve live operational data and explains risks including hallucinations, compliance gaps, security vulnerabilities, latency, inconsistent results and cascading failures.

## Source excerpt

AI evals for MCP in AIOps