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MCP-backed Terraform assistant with ephemeral-values compliance.

Project description

Terraform Guardrail MCP

CI

Terraform Guardrail MCP is a Python-based MCP server + CLI + minimal web UI that helps AI assistants and platform teams generate valid Terraform code and enforce ephemeral-values compliance. It targets multi-cloud teams and focuses on reducing configuration drift, secret leakage, and invalid provider usage. Live app: https://terraform-guardrail.streamlit.app/

What it does

  • MCP server that exposes provider metadata and compliance checks
  • CLI for scanning Terraform configs and state for sensitive leaks
  • Minimal web UI for quick scans and reports
  • Rules engine focused on ephemeral values, write-only arguments, and secret hygiene

Architecture

flowchart LR
    subgraph Interfaces
        CLI[CLI]
        MCP[MCP Server]
        WEB[Web UI]
    end

    subgraph Core
        SCAN[Compliance Engine]
        GEN[Snippet Generator]
    end

    REG[Terraform Registry]
    TF[Terraform CLI]

    CLI --> SCAN
    WEB --> SCAN
    MCP --> SCAN
    MCP --> GEN
    SCAN --> TF
    GEN --> REG
    MCP --> REG
flowchart TB
    INPUTS[Inputs: .tf, .tfvars, .tfstate] --> PARSE[Parse & Normalize]
    PARSE --> RULES[Apply Rules TG001-TG005]
    RULES --> REPORT[Findings + Summary Report]
    REPORT --> OUTPUT[CLI JSON / UI Render / MCP Response]

MVP scope (v0.1)

  • Scan .tf and .tfvars for sensitive values and missing ephemeral = true
  • Scan .tfstate for leaked sensitive values
  • Provider metadata retrieval for AWS and Azure via Terraform Registry
  • MCP server with scan_terraform and get_provider_metadata tools
  • Minimal web UI for uploading a file and viewing the report

Quickstart

python -m venv .venv
source .venv/bin/activate
pip install -e "[dev]"

# CLI scan
terraform-guardrail scan examples

# snippet generation
terraform-guardrail generate aws aws_s3_bucket --name demo

# MCP server (stdio)
terraform-guardrail mcp

# Web UI
terraform-guardrail web

CLI examples

# scan a directory
terraform-guardrail scan ./examples --format json

# scan state files too
terraform-guardrail scan ./examples --state ./examples/sample.tfstate

# enable schema-aware validation (requires terraform CLI + initialized workspace)
terraform-guardrail scan ./examples --schema

Web UI

Visit http://127.0.0.1:8000 and upload a Terraform file to view a compliance report.

Streamlit App

streamlit run streamlit_app.py

Live app: https://terraform-guardrail.streamlit.app/

Streamlit Cloud deployment

  1. Push this repo to GitHub.
  2. Create a new Streamlit Cloud app.
  3. Set the main file path to streamlit_app.py.
  4. Deploy (Streamlit will install from requirements.txt).

Release Links

Deployment Guide

See docs/streamlit_cloud.md for a detailed Streamlit Cloud walkthrough.

Diagrams

Mermaid diagrams render on GitHub and the Wiki. If you're viewing this on PyPI, use these links:

Release Checklist

  • Update version in pyproject.toml.
  • Update RELEASE_NOTES.md and CHANGELOG.md.
  • Commit changes and push to main.
  • Create and push a tag: git tag -a vX.Y.Z -m "vX.Y.Z" then git push origin vX.Y.Z.
  • Confirm GitHub Actions release workflow completed successfully.

Changelog Automation

This repo uses git-cliff to generate CHANGELOG.md.

git cliff -o CHANGELOG.md

Or run:

make changelog

Release Helpers

make release-dry VERSION=0.2.1
make version-bump VERSION=0.2.1

MCP tools (current)

  • scan_terraform: Run compliance checks over a path and optional state file.
  • get_provider_metadata: Fetch provider metadata from Terraform Registry (AWS + Azure).
  • generate_snippet: Generate Terraform snippets for common AWS/Azure resources.

Roadmap

  • Schema-aware code generation using provider schemas
  • fix command to apply safe rewrites for ephemeral values
  • Multi-environment policies and OPA-compatible output
  • Stack-aware orchestration and drift detection

License

MIT

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