CLI reference

Infrawise ships five commands, one per job: infrawise start to onboard (probe, generate config, analyze, connect your editor), infrawise analyze for an on-demand report, infrawise check as a CI/CD gate, infrawise serve to run the MCP server directly, and infrawise doctor to diagnose connectivity problems.

infrawise start

Probe the environment, generate infrawise.yaml if missing, analyze, write the MCP config file for your editor, then exit. This is the primary command — no config file is required on the first run.

infrawise start [options]

Flag	Default	Description
-c, --config <path>	infrawise.yaml	Path to config file
--claude	—	Write .mcp.json and open Claude Code
--cursor	—	Write .cursor/mcp.json and open Cursor
--vscode	—	Write .vscode/mcp.json (merging with existing servers) and open VS Code
--interactive	—	Run the guided setup wizard instead of auto-discovery
--rediscover	—	Delete infrawise.yaml and the .infrawise/ directory, then re-probe and re-analyze from scratch

Running infrawise start without an editor flag writes .mcp.json only (no editor is opened). Re-run any time your infrastructure changes to refresh the graph, or use --rediscover for a clean slate.

infrawise analyze

Force a full re-scan and print findings to stdout. Does not start the MCP server. Use this for scripted audits or to inspect findings without opening an editor.

infrawise analyze [options]

Flag	Default	Description
-c, --config <path>	infrawise.yaml	Path to config file
-r, --repo <path>	current dir	Repository to scan for service usage
--no-cache	—	Skip reading/writing the cache
-o, --output <path>	—	Save findings as a markdown report, e.g. report.md
--severity <level>	—	Only show findings at or above: high, medium, low

infrawise check

CI/CD gate. Runs a fresh analysis and exits with a non-zero code when findings reach the threshold severity, so it can block a deploy without an AI editor in the loop.

infrawise check [options]

Flag	Default	Description
-c, --config <path>	infrawise.yaml	Path to config file
-r, --repo <path>	current dir	Repository to scan for service usage
--fail-on <level>	high	Severity that fails the build: high, medium, low

# Block a deploy if any high-severity finding exists (exit 1)
infrawise check

# Stricter gate — fail on medium and above
infrawise check --fail-on medium

infrawise serve

Start the MCP server directly. Defaults to HTTP transport; pass --stdio for the transport editors use. Keeps running in the foreground.

infrawise serve [options]

Flag	Default	Description
-c, --config <path>	infrawise.yaml	Path to config file
--stdio	—	Use stdio transport (for editors via .mcp.json) instead of HTTP
-p, --port <n>	3000	HTTP port (HTTP only)

MCP endpoint (HTTP): POST http://localhost:<port>/mcp

Note

infrawise start --claude, --cursor, and --vscode write an MCP config that launches infrawise serve --stdio automatically. You rarely need to run serve directly. (Configs generated before this rename invoke a hidden infrawise stdio alias, which still works.)

infrawise doctor

Diagnostic escape hatch. Validates AWS credential resolution, tests connectivity to each configured service, and verifies the config file. Prints a pass/fail report per service and surfaces permission errors with the specific missing IAM action.

infrawise doctor

Run this when extraction comes up empty. No flags required beyond --config — it reads infrawise.yaml from the current directory.

infrawise --version

Print the installed Infrawise version.

infrawise --version

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FAQ

What is the difference between infrawise start and infrawise serve?

infrawise start runs a one-time scan, writes the MCP config file for your editor, then exits. Your editor picks up the config and manages the Infrawise process from there. infrawise serve starts the MCP server in the foreground — HTTP by default, or --stdio — and stays running until you stop it. Use serve for direct HTTP calls or non-stdio MCP clients.

How do I gate CI/CD on findings?

Use infrawise check. It runs a fresh analysis and exits 1 when any finding reaches --fail-on severity (default high), so it fails the pipeline step. Example: infrawise check --fail-on high.

When should I run infrawise analyze again?

Run infrawise analyze (or infrawise start) any time you add, remove, or significantly change AWS resources — new Lambda functions, new DynamoDB tables, new SQS queues, etc. The MCP tools your AI calls serve results from the in-memory graph built at startup; they do not re-scan on every call. For always-fresh data during active infrastructure work, use infrawise serve and restart it after changes.