MCP Directory

Cloudwright

Describe a cloud architecture in English; get Terraform, cost estimates, and compliance checks across AWS/GCP/Azure.

Unverified
stdio (local)
API key
Python
View repo 31

Add to your client

Copy the config for your MCP client and paste it into its config file.

Install / run
pip install cloudwright-ai-mcp

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "cloudwright": {
      "command": "cloudwright",
      "args": [
        "mcp"
      ]
    }
  }
}

Step-by-step guides: Add to Claude Desktop · Add to Cursor · Add to Windsurf

Before you start

  • Python 3.12+
  • pip install cloudwright-ai-mcp
  • ANTHROPIC_API_KEY (preferred) or OPENAI_API_KEY for the LLM-powered design/modify tools; cost, validate, analyze, and export run offline

About Cloudwright

Cloudwright turns a natural-language description of a cloud system into a typed architecture spec, a region-aware cost breakdown, a control-mapped compliance report, and deployable IaC (Terraform, OpenTofu, Pulumi TS/Python, CloudFormation) for AWS, GCP, Azure, and Databricks. The MCP server exposes 18 tools across 6 groups (design, cost, validate, analyze, export, session) so MCP-compatible agents can drive the full workflow. It runs over stdio by default (cloudwright mcp), supports an SSE transport for HTTP clients, and can be limited to a subset of tools with --tools.

Tools & capabilities (6)

design

Generate a structured cloud architecture spec from a natural-language description (design group; LLM-powered).

cost

Produce a region-aware, per-component cost breakdown across AWS, GCP, Azure, and Databricks with per-line pricing-confidence flags (cost group).

validate

Validate a spec against compliance frameworks (HIPAA, SOC 2, PCI-DSS, FedRAMP, GDPR, NIST, Well-Architected) and emit findings (validate group).

analyze

Run architecture analysis such as lint anti-patterns, quality scoring, blast-radius/SPOF analysis, drift, policy, and security checks (analyze group).

export

Export the spec to Terraform, OpenTofu, Pulumi (TypeScript or Python), or CloudFormation with safe-by-default hardening (export group).

session

Manage Cloudwright session state across tool calls (session group).

When to use it

  • Letting an AI agent design a compliant cloud architecture from a one-line prompt (e.g. 'HIPAA healthcare API on AWS with Postgres and Redis')
  • Generating per-component, region-aware cost estimates before any infrastructure is provisioned
  • Checking a design against HIPAA / SOC 2 / FedRAMP / PCI-DSS / NIST controls at design time
  • Exporting agent-designed architectures to deployable Terraform, OpenTofu, Pulumi, or CloudFormation

Security notes

The design and modify tools call an LLM and require ANTHROPIC_API_KEY (preferred) or OPENAI_API_KEY in the environment; cost, validate, analyze, and export run fully offline. Terraform/Pulumi exporters apply safe-by-default hardening (encryption, IMDSv2, locked-down S3, RDS deletion protection) and escape user-supplied config values against HCL injection. The `cloudwright plan` step does not pass the LLM key into the IaC subprocess.

Cloudwright FAQ

How do I install and run the MCP server?

Install with `pip install cloudwright-ai-mcp`, then run `cloudwright mcp` for all tools over stdio. Use `cloudwright mcp --tools design,cost` for a subset or `cloudwright mcp --transport sse` for HTTP clients.

Do I need an API key?

Only the LLM-backed design and modify tools need a key (ANTHROPIC_API_KEY preferred, or OPENAI_API_KEY). Cost, validate, analyze, and export work fully offline.

Which clients does it work with?

Any MCP-compatible client. The README provides a claude_desktop_config.json mcpServers block and notes the same shape works for Cursor and Cline.

Which clouds and IaC formats are supported?

AWS, GCP, Azure, and Databricks (112 service keys), with export to Terraform, OpenTofu, Pulumi (TypeScript or Python), and CloudFormation.

#cloud-architecture#terraform#infrastructure-as-code#cost-estimation#compliance#multi-cloud#aws#gcp#azure#devops

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