terravision: Cloud architecture diagrams in both directions: AI prompt or JSON to diagram, diagram to Terraform via MCP

by patrickchugh · MCP Server · ★ 1.7k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install terravision

pipx install terravision   # or: uv tool install terravision
claude plugin install terravision-cloud-diagrams@terravision

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 72/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillarchitecture-diagramarchitecture-diagram-generatorawsazurechatgptclaudecloud-architecturecloud-architecture-diagramcodex

Quick Facts

Stars1,660
Forks178
LanguagePython
CategoryMCP Server
LicenseAGPL-3.0
Quality Score72/100
Open Issues17
Last Updated2026-10-23
Created2022-03-13
Platformsaws, claude-code, cli, codex, mcp, python
Est. Tokens~17k

About terravision

TerraVision Turn Terraform or JSON files into professional cloud architecture diagrams with the official AWS, Azure and GCP icons 📖 Full documentation site → Watch a 4-Minute Intro What is TerraVision? TerraVision automatically converts your Terraform code, or a plain JSO

Compatible Skills

These tools work well together with terravision for enhanced workflows:

  • drawio-skill — semantic(0.47)+rare_topics+same_lang+similar_pop+shared_platform (65%)
  • aws-architecture-diagram-skill — semantic(0.40)+complementary+rare_topics+same_lang+shared_platform (63%)
  • excalidraw-skill — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (62%)
  • flowforge-skill — semantic(0.45)+complementary+rare_topics+same_lang+shared_platform (60%)
  • ArchUnitPython — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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