@quiq/cli

Official command-line connector for the Quiq platform — built for AI agents.

@quiq/cli (the quiq command) lets an AI agent operate Quiq on a person's behalf: search and analyze conversations, drive funnels, read account topology, and more — over Quiq's typed RPC surface. It is official Quiq software, published and maintained by Quiq.

What this is (and isn't)

• A connector, not a typical CLI. Think of it as a plugin for the Quiq platform — closer in spirit to an MCP server than to a hand-run command-line tool, but with a higher ceiling: it exposes Quiq's full typed RPC surface and adds filesystem niceties (large results spill to disk, presigned artifacts stream straight to files) that keep an agent's context lean.
• Meant for AI, on behalf of humans. The ergonomics target an autonomous agent invoking commands, not a person typing them. A human sets up and approves a session; the agent drives it.
• Safe to install and run. Apache-2.0 licensed, a single runtime dependency (commander), no install/postinstall scripts, and the full source ships in the package. Every bit of platform access is gated behind an explicit, human-approved, per-session credential — the CLI cannot reach anything a user has not granted it.

Install

npm install -g @quiq/cli

Requires Node.js ≥ 20.

Quickstart

# 1. Establish a session (the user approves it once, in the Quiq web app)
quiq session start --host <your-quiq-domain>   # prints an approval URL
quiq session complete --code <code>            # after the user approves

# 2. Orient — the model and conventions for driving the surface
quiq orientation --session <id>                # (or just `quiq --session <id>`)

# 3. Discover the surface — the methods available and their I/O types
quiq schema --session <id>

From there, the orientation and schema are self-describing: they tell the agent what it can do, how to invoke it, and how results come back. This README stays deliberately thin on purpose — that guidance lives on the server and evolves without a CLI release. Read the orientation before authoring anything.

How it works

• Dynamic over the platform. Nothing is hardcoded: the surface derives entirely from the platform's live, typed schema, so new capabilities appear without a CLI update.
• Context-friendly. Large responses and artifacts are kept out of the model's context — spilled or streamed to disk for the agent to read on demand — rather than inlined into the transcript.
• Session-scoped and explicit. Each session carries its own bearer credential, and every command targets an explicit session — never a silent default.

License

Apache-2.0 — see LICENSE.