MCP Server Terraform

mcp-server-terraform

A Model Context Protocol (MCP) server that lets Claude manage Terraform infrastructure through natural language.

Run plans, apply changes, inspect state, and diagnose failures — all from a Claude conversation.

What it does

Instead of switching to a terminal to run terraform plan, you can ask Claude:

"Plan the changes in /infra/staging and explain what will change"

"Apply it — but only if no resources will be destroyed"

"Show me all the outputs from the prod workspace"

"Something broke after the last apply — diagnose it"

The server translates these into real terraform CLI commands on your machine, with a built-in safety confirmation flow before any destructive operation runs.

Tools

Plan risk & cost summary

Every plan (and every apply preview) is analyzed via terraform show -json and annotated with a structured summary — destroyed resources are called out, and always-on resources that commonly cause bill shock are flagged with rough monthly costs:

── Plan Summary ──

• 3 create, ~ 1 update, - 0 destroy, ± 0 replace

💸 EXPENSIVE — always-on resources being created: ⚠ aws_nat_gateway.main (~$32/month + data processing if left running) Remember to tf_destroy when you're done experimenting.

Cost-flagged resource types include NAT gateways, load balancers, EKS/AKS/GKE control planes, RDS/Cloud SQL instances, ElastiCache, Redshift, MSK, and Azure Firewall (~$900/month!).

Drift detection

tf_drift runs a refresh-only plan and reports resources that were changed outside Terraform (e.g. manually in the cloud console), with the changed attribute names and remediation options.

Audit logging

Set AUDIT_LOG_PATH to a file path and every tool call is appended as a JSON line with timestamp, tool name, outcome, and duration. Variable values are always redacted (db_password= ) — only names are logged.

Confirmation flow

tf_apply and tf_destroy use a two-step safety flow:

1. First call (no confirmed) → runs terraform plan, shows the diff, does nothing else
2. Second call (confirmed: true) → actually applies or destroys

Claude is instructed to never pass confirmed: true without first presenting the plan to you.

Prompt

The server exposes a /tf-diagnose prompt that guides Claude through a systematic 5-step diagnosis of plan or apply failures.

Prerequisites

• Node.js 18 or later
• Terraform CLI on your PATH
• Claude Desktop (or any MCP-compatible client)

Installation

No install needed — run it straight from npm:

npx @rajsir/mcp-server-terraform

Or, for development, from source:

git clone https://github.com/RajeevSirohi/mcp-server-terraform.git

cd mcp-server-terraform npm install npm run build

Claude Desktop setup

Add to your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{

"mcpServers": { "terraform": { "command": "npx", "args": ["-y", "@rajsir/mcp-server-terraform"] } } }

(If running from source instead, use "command": "node" with "args": ["/absolute/path/to/dist/index.js"].)

Restart Claude Desktop. You should see a hammer icon indicating tools are available.

Usage

Once connected, just talk to Claude about your Terraform workspaces in plain language. Some examples:

First time in a new workspace

"Initialize the terraform config in C:\infra\staging and check if I'm logged into the right cloud accounts"

Claude runs tf_init, then tf_preflight — if you're not authenticated it tells you exactly which command to run (az login, aws configure, ...).

The everyday plan → review → apply loop

"Plan the changes in C:\infra\staging and explain what will change"

You get the plan diff plus a summary: how many resources created/updated/destroyed, anything destructive called out explicitly, and cost warnings for expensive always-on resources.

"Looks good, apply it"

Claude shows the plan preview one more time and asks for your confirmation — nothing is applied until you say yes. This two-step gate is built into the server itself, not just the prompt, so Claude *cannot* skip it.

Checking on your infrastructure

"Did anyone change anything outside terraform in the prod workspace?"

tf_drift compares state against reality and reports what was modified in the console, with options to accept or revert.

"Show me all the outputs" · "List everything in state" · "What workspaces exist?"

Learning / experimenting (e.g. cert prep)

"Apply the VPC lab in C:\labs\vpc, and when I say 'done' destroy everything"

The cost flags are your friend here — if a lab creates a NAT gateway or EKS cluster, the plan summary warns you what it costs per month if forgotten:

💸 EXPENSIVE — always-on resources being created:

⚠ aws_nat_gateway.main (~$32/month + data processing if left running) Remember to tf_destroy when you're done experimenting.

Fixing things

"terraform plan is failing in C:\infra\staging — diagnose it"

The /tf-diagnose prompt walks Claude through validate → providers → plan → state → outputs systematically. There's also /tf-login for step-by-step authentication setup per provider.

"Import the S3 bucket my-legacy-bucket into state as aws_s3_bucket.legacy"

"Taint the web server so it gets recreated on the next apply"

Recommended setup for shared or cautious environments

Run with ALLOW_ONLY_NON_DESTRUCTIVE_TOOLS=true (see Safety modes below) so apply/destroy are unavailable entirely, and set AUDIT_LOG_PATH so every operation is logged.

Safety modes

Control which tools are available via environment variables:

Example — read-only mode:

{

"mcpServers": { "terraform": { "command": "node", "args": ["/path/to/dist/index.js"], "env": { "ALLOW_ONLY_NON_DESTRUCTIVE_TOOLS": "true" } } } }

Development

npm run dev       # watch mode (recompiles on save)

npm test # run tests npm run build # production build

Project structure

src/

index.ts # MCP server entry point, tool registration config/ # (reserved for future config/telemetry) models/ common-parameters.ts # Shared Zod schemas security/ tf-flags.ts # Dangerous flag blocking tools/ tf-init.ts tf-validate.ts tf-plan.ts tf-apply.ts # Two-step confirmation flow tf-destroy.ts # Two-step confirmation flow tf-output.ts tf-state.ts tf-workspace.ts utils/ terraform-runner.ts # Core exec wrapper, workspace switching prompts/ index.ts # /tf-diagnose prompt tests/ tf-flags.test.ts tf-apply.test.ts

Adding a new tool

1. Create src/tools/tf-yourcommand.ts — export a *Schema const and an async handler function
2. Import both in src/index.ts
3. Add the schema to readonlyTools or destructiveTools array
4. Add a case in the CallToolRequestSchema handler switch

Roadmap

• Terraform Cloud / Enterprise API support (Phase 2)
• OpenTelemetry tracing
• SSE / streamable HTTP transport for remote deployments
• Docker image on GitHub Container Registry
• Plan risk & cost analysis
• Drift detection
• Import / taint / untaint / refresh
• Audit logging
• CI (build, test matrix, e2e against real terraform)

Contributing

See CONTRIBUTING.md.

License

MIT — see LICENSE.