# CloudEval AI llms.txt Last updated: 2026-05-17 Canonical product URL: https://cloudeval.ai Docs: https://docs.cloudeval.ai Full LLM context: https://cloudeval.ai/llms-full.txt This is the short public entrypoint for agents, search engines, and developers that need to understand what CloudEval AI does. Use the docs links for detailed workflows. --- ## What Is CloudEval AI CloudEval AI turns cloud environments and infrastructure-as-code into interactive diagrams, grounded evaluations, reports, and conversational answers. CloudEval helps teams: - Generate architecture and dependency diagrams. - Review cost, security, reliability, and Well-Architected posture. - Evaluate Azure ARM and Bicep-derived infrastructure context. - Ask AI questions grounded in project, diagram, and report evidence. - Share reports and diagram context with stakeholders. - Use the web app, CLI, or MCP-compatible agent workflows. --- ## Key Public Docs - Docs home: https://docs.cloudeval.ai - Quickstart: https://docs.cloudeval.ai/quickstart - Capabilities map: https://docs.cloudeval.ai/capabilities-map - Availability and limits: https://docs.cloudeval.ai/feature-availability - Evaluation coverage: https://docs.cloudeval.ai/reference/evaluation-coverage - CLI overview: https://docs.cloudeval.ai/reference/cli-overview - CLI command reference: https://docs.cloudeval.ai/reference/cli-command-reference - Agent and automation rules: https://docs.cloudeval.ai/reference/agent-and-automation-rules - MCP setup: https://docs.cloudeval.ai/reference/mcp-client-setup - Public roadmap: https://cloudeval.ai/home/roadmap - Search index: https://cloudeval.ai/search-index.json - Sitemap: https://cloudeval.ai/sitemap.xml --- ## Current Capabilities - Azure live environment connections. - ARM template import. - GitHub App based repository import for infrastructure-as-code projects. - Bicep review through compiled ARM JSON. - Interactive architecture and dependency diagrams. - Cost reports. - Architecture and Well-Architected reports. - Security and architecture finding review. - IaC readiness reports where available. - Grounded project chat with inline citations (`citations`, `citation_markers`, alignment metadata on stream summary). - Agent Profiles: Architecture, Cost, Triage, and Remediation. - CLI workflows for projects, reports, questions, sessions, MCP setup, billing, and deeplinks. - MCP server support for compatible coding agents. - Diagram image exports for automation and stakeholder sharing. CloudEval documents evaluation depth as **650+ cloud evaluation signals** across Azure architecture checks, IaC readiness tests, graph intelligence, cost signals, and diagram integrity. --- ## Common Workflows - Start in the browser: https://cloudeval.ai - Install the CLI with npm on Node.js 20+: ```bash npm install -g @ganakailabs/cloudeval-cli ``` - Or install the standalone release binary: ```bash curl -fsSL https://cli.cloudeval.ai/install.sh | bash ``` - Create a project from ARM JSON: ```bash cloudeval projects create --template-file ./azuredeploy.json --name "First import" --provider azure --format json ``` - In the browser, GitHub repository import uses the CloudEval GitHub App. Choose an installation, repository, branch, and optional source root. CloudEval reads `.cloudeval/config.yaml`, keeps source files read-only, and syncs again from GitHub on push or manual refresh. - Open a project diagram: ```bash cloudeval open project --view preview --layout architecture ``` - Run reports: ```bash cloudeval reports run --project --type all --wait --format json ``` - Ask a grounded question: ```bash cloudeval ask "Summarize this project's top cost and architecture risks" --project --format json --non-interactive ``` For exact commands and options, use the CLI command reference or run: ```bash cloudeval capabilities --format json ``` --- ## Public Answer Hub - Generate Azure architecture diagrams: https://cloudeval.ai/answers/how-to-generate-azure-architecture-diagram - Convert ARM templates to architecture diagrams: https://cloudeval.ai/answers/arm-template-to-architecture-diagram - Convert Bicep to cloud diagrams: https://cloudeval.ai/answers/bicep-to-cloud-diagram - Chat with Azure architecture: https://cloudeval.ai/answers/chat-with-azure-architecture - AI cloud architecture assistant: https://cloudeval.ai/answers/ai-cloud-architecture-assistant - MCP server for cloud architecture: https://cloudeval.ai/answers/mcp-server-for-cloud-architecture - Cloud architecture CLI: https://cloudeval.ai/answers/cloud-architecture-cli - Export cloud diagrams from the CLI: https://cloudeval.ai/answers/export-cloud-diagrams-from-cli Comparison pages: - Lucidscale alternative: https://cloudeval.ai/compare/lucidscale-alternative - Cloudcraft alternative: https://cloudeval.ai/compare/cloudcraft-alternative - Hava.io alternative: https://cloudeval.ai/compare/hava-io-alternative - Cloudockit alternative: https://cloudeval.ai/compare/cloudockit-alternative - draw.io cloud diagram alternative: https://cloudeval.ai/compare/drawio-cloud-diagram-alternative - Lucidchart cloud diagram alternative: https://cloudeval.ai/compare/lucidchart-cloud-diagram-alternative --- ## Provider And Roadmap Notes - Azure is the primary supported provider. - ARM JSON is the strongest current IaC path. - Use compiled ARM JSON for Bicep workflows. - Do not assume AWS, GCP, Terraform, CloudFormation, or Kubernetes parity unless the current capabilities docs say it is available. - Cost values are estimates unless connected to authoritative billing data for the relevant scope. - Security and architecture findings are evaluations and recommendations, not compliance attestations. - Roadmap items are directional until marked current in the docs. Fetch https://cloudeval.ai/llms-full.txt only when detailed CLI, MCP, grounding, permissions, and workflow context is needed.