Updated May 12, 2026
What is an AI cloud architecture assistant?
Quick answer
An AI cloud architecture assistant should answer from project context, not from a blank prompt.
Cloudeval combines diagrams, files, live Azure sync, reports, CLI workflows, and MCP-compatible access so teams can ask better architecture questions.
What you can expect
A practical path from source input to diagram, report context, docs, exports, and the first AI question to ask.
Start here
Use this to
Use AI to review architecture without losing source context or evidence.
Best source to use
Give the assistant a Cloudeval project, report, diagram, or docs page so the answer can reference real context.
What you need
- A Cloudeval project or docs context the assistant can use.
- Reports or diagrams for questions that need evidence.
- Scoped credentials for automation or agent access.
What you get
- Project-aware architecture answers.
- Source-aware recommendations.
- Agent or CLI workflows for repeated review tasks.
Fastest path to a useful result
- 1Create or open a Cloudeval project.
- 2Run a report or open a diagram.
- 3Ask a focused architecture question.
- 4Use CLI or MCP when the workflow needs automation.
Helpful docs
When this works best
Use this when you want AI answers tied to Cloudeval projects, reports, diagrams, CLI workflows, or MCP access rather than a generic chatbot response.
Decision guide
| Check | Cloudeval path | Note |
|---|---|---|
| Context | Project, diagram, report, docs, CLI, and MCP context. | Better context means better answers. |
| Best question | Ask what changed, what is risky, or what evidence supports a finding. | Avoid vague “is this good?” prompts. |
| Automation | Use CLI or MCP for repeatable tasks. | Use scoped access keys. |
| Human review | Reviewers still validate important decisions. | AI helps prepare the review; it does not own it. |
Who this is for
- Developer platform teams
- Cloud architects
- AI-assisted engineering teams
- Consultants
How it works
- 1Connect Cloudeval to a project source such as ARM/Bicep output or live Azure sync.
- 2Use diagrams and reports to establish a project baseline.
- 3Ask focused questions about risks, dependencies, costs, and remediation options.
- 4Let agents use MCP tools where configured to retrieve Cloudeval project and report context.
- 5Use CLI workflows for repeatable project, report, export, and ask commands.
- 6Review evidence and freshness before making architecture decisions.
Assistant for architecture review
A platform team can ask which resources are exposed, which findings need review, which report supports a recommendation, and how to export the current diagram for review.
Cloudeval is useful when AI answers and project context stay connected.
Terminal and agent workflow
- Cloudeval CLI supports setup, diagnostics, projects, reports, sessions, MCP, billing, and frontend deeplinks.
- Cloudeval MCP tools let compatible agents query product documentation and project/report context depending on configuration.
- Scoped access keys are preferred for CI and agent automation.
How to trust the result
- Ask which resource, report, or diagram element supports the answer when it affects a decision.
- Check sync time and report confidence before sharing recommendations.
- Use narrow questions for specific resources, findings, or dependencies.
FAQ
How is this different from a generic chatbot?
Cloudeval answers can use project resources, diagrams, reports, and source details, while a generic chatbot usually lacks current infrastructure context.
Can AI agents use Cloudeval?
Yes.
Cloudeval exposes MCP workflows and CLI commands that compatible agents can use when configured with appropriate permissions.
Does Cloudeval replace architecture review?
No.
It helps teams gather diagrams, findings, and evidence faster, but reviewers should still validate important decisions.
Related pages
Build this workflow in Cloudeval
Start with a Cloudeval Azure project, then connect diagrams, reports, source links, CLI automation, and MCP-compatible agent workflows around the same source of truth.
