Merge for Workforce CLI (mfw)

A command-line tool for Merge for Workforce employees: log in with your IdP, get a Gateway credential, and use your provisioned models and tools from the terminal.

Install

pipx install merge-workforce   # recommended (isolated env, puts `mfw` on PATH)
pip install merge-workforce    # alternative

pipx keeps the tool in its own environment and avoids the "externally-managed-environment" error a plain pip install hits on modern Python. One-time setup: brew install pipx && pipx ensurepath (macOS) or python3 -m pip install --user pipx && pipx ensurepath (Linux). Update later with pipx upgrade merge-workforce. Requires Python 3.10+.

Before the first PyPI release you can install straight from the repo: pipx install git+ssh://git@github.com/merge-api/merge-workforce-cli.git.

Quickstart

mfw login --gateway-url https://ah-api.merge.dev   # opens your browser to sign in
mfw setup                                          # provision this device's Gateway credential
mfw models                                         # list the models you can use
mfw ask  -m openai/gpt-4o-mini "hello"             # one prompt to a chosen model
mfw chat -m openai/gpt-4o-mini "use my tools to …" # an agent that can call your provisioned tools

Set MFW_GATEWAY_URL once and you can drop --gateway-url from every command.

You must be a provisioned employee. mfw setup mints your key only once your admin has activated Merge for Workforce and your group has a Gateway project. If setup returns "your admin has not finished setting up Merge Gateway for your group yet", that setup isn't complete — it's not a CLI error.

Commands

Run mfw --help, or mfw <command> --help for details on any one.

The Gateway routes and bills every call and enforces your allowlist, so a model or tool you aren't provisioned for comes back as a request error, never a silent fallback.

Usage with AI agents

Two ways to give an AI agent your provisioned models and tools, both governed by your org:

• mfw chat is a built-in agent — it drives a model through the Gateway and calls your provisioned tools over MCP, no other client needed.

• mfw mcp hands your tools to an external MCP client (Claude Code, Cursor, any SDK agent). Write the config where the client reads it:

  mfw mcp --write .mcp.json     # Claude Code picks this up from the project root
  

  The config points the client at the backend's MCP endpoint with a short-lived token, so the agent calls tools as you, exactly as the console governs them. Re-run when the token lapses.

For OpenAI-SDK tools, mfw run -- <command> injects OPENAI_API_KEY / OPENAI_BASE_URL pointed at the Gateway, so the tool routes through it unchanged.

How it works

• Login is OAuth 2.0 Authorization Code + PKCE with a loopback redirect (RFC 8252): the public client merge-workforce-cli (no secret on the laptop), your browser → <gateway>/o/authorize/ → IdP login + consent → code returns to http://localhost:{9410-9419}/callback → exchanged at <gateway>/o/token/. The access token is stored in ~/.mfw/credentials.json (0600).
• Setup exchanges that token for a per-device Gateway API key (~/.mfw/gateway_credential.json), the same per-device path the desktop client uses — independently revocable, with spend attributed to you.
• Models are the maintained /v1/responses surface; chat connects your provisioned tools over the backend's OAuth-authed /mcp/ endpoint and runs the function-calling loop for you.