meticulous-cli

Meticulous CLI

The meticulous CLI records user sessions and replays them to catch visual regressions. It is installed as part of @alwaysmeticulous/cli.

Before starting, run the meticulous-cli-update skill to ensure the Meticulous CLI and skills are up to date — unless it has already run earlier in this conversation, in which case skip it.

Invocation

meticulous <command> [options]

The skills assume meticulous is on PATH. The meticulous-cli-update skill installs it globally via npm install --global @alwaysmeticulous/cli@latest if missing. It can also be invoked as npx @alwaysmeticulous/cli when installed locally per-project.

Command Groups

Command	Purpose
agent	Read, analyse, and trigger test runs — the agent-facing commands, also exposed on the MCP server
auth	Authenticate with Meticulous (login, whoami, logout, project selection)
debug	Set up AI-ready debug workspaces for investigating replay diffs and replays
download	Download sessions, replays, and test runs locally
local	Find sessions relevant to the current branch's code changes
project	Inspect the project you're authenticated against
simulate / replay	Replay a recorded session against a URL
schema	Output the CLI command schema as JSON (for agent/programmatic use)

See the reference for each group for full option details:

• references/agent.md
• references/auth.md
• references/debug.md
• references/download.md
• references/local.md
• references/project.md
• references/simulate.md
• references/schema.md

Global Options

These options are accepted by every command:

Option	Type	Default	Description
--logLevel	string	info	Log verbosity: trace, debug, info, warn, error, silent
--dataDir	string	~/.meticulous	Directory where sessions, replays, and other data are stored
--jsonArgs	string	—	Pass all options as a JSON string (useful for programmatic/agent invocation)

--rawJson is a deprecated alias for --jsonArgs. --dryRun is not global — it is available only on the commands that perform actions (e.g. the ci / agent run-triggering and upload commands, and simulate); check the command's reference or meticulous schema <command>.

Authentication

Commands authenticate via OAuth. The login token is stored on disk and reused across sessions — in an interactive terminal, a command that needs auth opens a browser sign-in automatically; without a TTY (the usual agent case) it fails and tells you to run meticulous auth login. Run meticulous auth whoami to see the current state. Project-scoped commands also need a default project, set at login or with meticulous auth set-project. See references/auth.md.

An API token (via --apiToken or the METICULOUS_API_TOKEN environment variable, scoped to a specific organization/project) is also supported, and is the way to authenticate in non-interactive contexts such as CI. Some agent platforms instead inject a bearer credential into outbound requests to app.meticulous.ai; that works too, and auth whoami reports it as credentials injected at request time.

MCP server

The agent commands are also exposed as tools on a hosted MCP server at https://app.meticulous.ai/api/mcp, so an MCP-enabled client (Claude Code, Cursor, Codex) can call them directly rather than shelling out to the CLI. Most read/analysis commands map to a get_<command> tool that returns the same data as the CLI command's --json output — for example agent test-run-diffs ⇄ get_test_run_diffs, agent dom-diff ⇄ get_dom_diff, and download session ⇄ get_session_data. The two mutating commands (upload-build, trigger-test-run) also have MCP tools, but not 1:1 — see references/agent.md for the full mapping, including that important difference. Connect with just the endpoint URL (browser OAuth on first use). The skills are written in terms of the CLI; substitute the matching tool where noted if you have the MCP server connected — but note MCP tools never infer git context (commitSha/baseSha/diff), unlike the CLI, so always pass those explicitly when using MCP.

Example

# Print schema for all commands (agent use)
meticulous schema

# Run a single replay locally
meticulous simulate --sessionId=<id> --appUrl=http://localhost:3000