qspro-cli
Command-line client for QuickSilver Pro — one OpenAI-compatible API for Claude, GPT, Gemini, DeepSeek, Qwen, Kimi and Muse chat plus FLUX images, on a single balance. Agent-friendly: every command emits --json with stable exit codes.
Links
README
From the repo.
QuickSilver Pro CLI
qsp — a command-line client for QuickSilver Pro, one OpenAI-compatible API for frontier and open-source LLMs (Claude, GPT, Gemini, Grok, GLM, DeepSeek, Qwen, Kimi, Muse) and FLUX text-to-image — all billed to a single balance. Open-source chat models run up to 20% below OpenRouter.
Designed to be AI-agent friendly: data commands accept --json for structured output, exit codes are reliable, and the API surface is intentionally small.
Related repos
QuickSilver Pro is developed in three repositories under machinefi:
| Component | Repo | Visibility |
|---|---|---|
CLI — qsp command-line client (this repo) | qspro-cli | Public |
| Backend — API gateway + billing | qspro-backend | Private |
| Frontend — landing + dashboard | qspro-frontend | Private |
End-user site: https://quicksilverpro.io.
Install
pip install quicksilverpro
Or run it with no install:
uvx quicksilverpro chat "Write me a haiku" # via uv — fetches Python for you: https://docs.astral.sh/uv/
pipx run quicksilverpro chat "Write me a haiku" # via pipx (needs Python 3.10+)
On Windows, uvx is the simplest path — uv downloads a suitable Python automatically. On macOS you can also brew install machinefi/qspro/qspro.
Python 3.9+. Also exports itself as quicksilverpro if you prefer the long name.
Quick start
qsp init # opens dashboard to get a key, stores it locally
qsp chat "Write me a haiku" # one-shot streaming chat (deepseek-v4-flash by default)
qsp image "a fox in the snow" # text-to-image, saves a file (flux.2-pro by default)
qsp balance # current credits
qsp models # supported models with prices & context length
qsp status # live per-model latency
Commands
| Command | Purpose |
|---|---|
qsp init [--email X] [--key sk-...] | Sign in (browser walkthrough) or paste an existing key |
qsp logout | Forget locally-stored key |
qsp whoami [--json] | Show signed-in email + balance |
qsp balance [--json] | Credit balance + lifetime spend |
qsp models [--json] | Available models + pricing + context length |
qsp chat "PROMPT" [-m MODEL] [-s SYS] [--max-tokens N] [--temperature F] [--no-stream] [--json] | One-shot completion, streams to stdout by default |
qsp image "PROMPT" [-m MODEL] [-o FILE] [--size WxH] [-n N] [--json] | Text-to-image; saves to a file (flux.2-pro by default) |
qsp usage [-n 10] [--json] | Recent calls + aggregate per-model |
qsp status [--json] | Live health of API + per-model probes |
qsp keys list [--json] | Your API keys |
qsp keys create ALIAS [--monthly-limit USD] [--json] | Create a new key with optional spend cap |
qsp keys delete ALIAS [-y] | Delete a key (confirmation prompt unless -y) |
qsp pay {5,20,50} | Opens Stripe checkout for a credit top-up |
AI-agent usage
Data commands (chat, image, models, balance, usage, status, keys list/create, whoami) support --json and print OpenAI-shaped JSON to stdout with errors on stderr.
qsp models --json | jq '.[].id'
qsp usage --json | jq '.totals.cost'
qsp chat "Summarize: $DOCUMENT" --json --no-stream | jq -r '.choices[0].message.content'
qsp image "a fox in the snow" -o fox.png # writes fox.png
qsp image "a fox in the snow" --json | jq -r '.data[0].b64_json' | base64 -d > fox.png
Exit codes: 0 success · 1 remote/operational error · 2 usage / auth error.
Config
Key stored at ~/.config/quicksilverpro/config.json (chmod 600). Override with:
QSP_API_KEY— use this key directly, ignore stored configQSP_API_URL— defaulthttps://api.quicksilverpro.io/v1QSP_AUTH_URL— defaulthttps://pay.quicksilverpro.ioQSP_MODEL— default model forqsp chatQSP_IMAGE_MODEL— default model forqsp imageQSP_CONFIG_DIR— where to store configQSP_HTTP_TIMEOUT— seconds, default 60 (image requests default to 180)
Use the openai SDK directly
You don't need this CLI to use QuickSilver Pro. The OpenAI Python / Node / Swift SDKs work with only a base_url change:
from openai import OpenAI
client = OpenAI(
base_url="https://api.quicksilverpro.io/v1",
api_key="sk-...", # your QuickSilver Pro key
)
r = client.chat.completions.create(
model="deepseek-v4-flash",
messages=[{"role": "user", "content": "Hello"}],
)
See quicksilverpro.io/dashboard#quickstart for JS / Swift / curl.
License
MIT.
QuickSilver Pro is a product of MachineFi Inc. (68 Willow Rd, Menlo Park, CA).
Collected info
- ★ 3 stars
- ⎇ 1 forks
- Language: Python
- Source updated: 8/25/2026
Config for your environment
Replace {MCP_ENDPOINT_URL} with this MCP’s endpoint URL (from its repo or docs above). No API key — you connect directly.
Tool
OS
Config file: ~/.cursor/mcp.json
{
"mcpServers": {
"mcp-server": {
"url": "{MCP_ENDPOINT_URL}"
}
}
}Paste into mcpServers in the config file. Restart Cursor after saving.
If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.