How do I use qjtrader-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@qjtrader-mcp Place a simulated buy order for 1 CRAU26 at 97.00" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

qjtrader-mcp

Official

by QJTrader

Overview Schema Related Servers Score Discussions

Python

Remote

qjtrader-mcp

Model Context Protocol server for the QJ Trader AI Trading APIs. Point your LLM at your QJ credential and it can watch live Canadian market data and place simulated orders — no code, no manual API testing.

Built on the official qjtrader Python SDK. Talk to it from Claude Code, Claude Desktop, or any MCP-capable client:

"Subscribe to CA:RY and MX:CRAU26, show me the books, then buy 1 CRAU26 at 97 in the sandbox and tell me the fill."

Safety model — AI trades simulated by default

Order-mutating tools (place_order, cancel_order, replace_order, cancel_all) run against a sandbox credential by default and return simulated fills. A live credential is refused unless you explicitly opt in. The server never sniffs this off the wire (the protocol doesn't expose it) — you declare it:

`QJ_ENV`	Read tools (quotes/depth/status)	Order tools
`sandbox`	✅	✅ simulated
`live`	✅	⛔ unless `QJ_MCP_ALLOW_LIVE=1`
(unset)	✅	⛔ (fail-safe: unknown is treated as live)

Every tool result is prefixed with an environment tag ([SANDBOX] / [LIVE — REAL MONEY] / [ENV UNKNOWN]), and order quantity is capped client-side by QJ_MCP_MAX_QTY (default 25).

Related MCP server: Aster MCP Server

Install

Get a free sandbox credential (no approval) at console.qjtrader.ai.

Once published to PyPI, the zero-install path is:

uvx qjtrader-mcp        # or: pipx run qjtrader-mcp

Until then (or for local development against the SDK checkout):

# from the qjtrader-mcp/ directory, with the qjtrader-python sibling checked out:
uv sync && uv run qjtrader-mcp          # uv resolves qjtrader from ../qjtrader-python
# — or with pip —
pip install -e ../qjtrader-python -e .
qjtrader-mcp

Configure your client

Claude Code

claude mcp add qjtrader -- uvx qjtrader-mcp
# then set the credential + environment for the server:
claude mcp add qjtrader \
  -e QJ_CLIENT_ID=your-client-id \
  -e QJ_CLIENT_SECRET=your-client-secret \
  -e QJ_ENV=sandbox \
  -- uvx qjtrader-mcp

Claude Desktop / generic stdio

Add to your MCP config (claude_desktop_config.json or equivalent):

{
  "mcpServers": {
    "qjtrader": {
      "command": "uvx",
      "args": ["qjtrader-mcp"],
      "env": {
        "QJ_CLIENT_ID": "your-client-id",
        "QJ_CLIENT_SECRET": "your-client-secret",
        "QJ_ENV": "sandbox"
      }
    }
  }
}

The console's "Connect your AI" panel generates these blocks pre-filled, including QJ_ENV=sandbox.

Tools

Tool	Kind	Description
`session_info`	read	Environment, whether order actions are allowed, endpoints, authenticated user. Call first.
`get_quote`	read	Top-of-book (best bid/ask) for one or more symbols
`get_depth`	read	Level-2 order book for a symbol (venue-tagged on consolidated books)
`watch`	read	Sample the live stream for a bounded window; returns a digest + last messages
`list_orders`	read	Open orders + session state
`place_order`	write	Submit a limit order and wait for a terminal state
`cancel_order`	write	Cancel a working order by `cid`
`replace_order`	write	Amend a working order's qty/price
`cancel_all`	write	Cancel every working order (kill switch)
`explain_symbol`	util	Parse/explain a symbol (prefix + root + venue), offline
`read_events`	read	Order journal — cross-order event history; post-trade analysis & strategy debugging
`get_history`	read	Historical OHLCV bars (1s/1m); sandbox = deterministic synthetic days
`get_stats`	read	Server digest for a symbol: VWAP, spread, volume, realized vol (a digest, not a dump)
`get_chain`	read	Options chain snapshot for an underlying/expiry (latest or historical)
`compare`	read	Rank a digest metric (vwap/volume/realized_vol/spread_mean) across symbols

The read_*/get_* research tools make the LLM a quant developer: analyse the market and debug the strategy it wrote, without touching the production order path.

Configuration reference

Env var	Purpose	Default
`QJ_CLIENT_ID` / `QJ_CLIENT_SECRET`	credential	— (required)
`QJ_ENV`	`sandbox` \| `live` — declares the environment	unset → treated as live
`QJ_MCP_ALLOW_LIVE`	set `1` to authorize live order actions	off
`QJ_MCP_MAX_QTY`	client-side max order quantity	`25`
`QJ_DATA_HOST` / `QJ_ORDERS_HOST`	endpoint overrides	public QJ hosts
`QJ_CA_FILE`	pin a CA/cert (pilot order endpoint)	none

License

Apache-2.0. See LICENSE.

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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