Varrd
About
VARRD is the Cursor for trading — an AI-native quant research engine that turns domain knowledge into statistically validated trading edges. Describe any idea in plain English, and VARRD loads real market data, builds the pattern, and runs institutional-grade statistical tests to
Details
- Transport
- SSE
Explore
- Scans live strategies for actionable signals (free)
- Researches trading ideas via multi‑turn AI workflow (~20–30¢)
- Discovers edges autonomously (~20–30¢)
- Enforces statistical guardrails (K‑penalty, multiple testing correction)
- Supports futures (CME), US equities, and crypto (Binance)
- Provides exact entry, stop‑loss, and take‑profit prices
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
VarrdCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
``python
from varrd import VARRD
v = VARRD() # auto-creates free account
r = v.research("show me the trade setup", session_id=r.session_id)
Add to your MCP config:
`json`
{
"mcpServers": {
"varrd": {
"transport": {
"type": "streamable-http",
"url": "https://app.varrd.com/mcp"
}
}
}
}
That's it. Your AI can now scan strategies, research ideas, and get trade setups — with all the statistical guardrails enforced automatically.
---
The first time you use VARRD (via Python, CLI, or MCP), an account is automatically created for you. You'll receive a passkey — a unique key that looks like VARRD-XXXXXXXXXXXXXXXX. This is your identity.`
VARRD account created.
Your passkey: VARRD-A3X9K2B7T4M8P1Q6
Saved to: ~/.varrd/credentials
Keep this passkey safe. To see your strategies in the
browser, go to app.varrd.com and link your agent using
this passkey with an email and password.
How it works:
1. First use — account auto-created, passkey saved to , free credits granted`
2. Ongoing use — all your strategies, test results, and credits are tied to this passkey
3. Link to browser — go to app.varrd.com, click "Link your AI agent", enter your passkey with an email and password. Your agent's strategies and credits merge into your account.
4. After linking — sign in with email/password to see everything your agent discovered, or keep using the CLI/API with the same passkey. Both work.
Keep your passkey safe. It's the key to your strategies. If you lose it before linking to an email, your work is gone. After linking, your email and password are your login — the passkey is just for the initial connection.
You can also pass a key explicitly:
python`
v = VARRD(api_key="your-key") # Python
bash``
varrd --key your-key scan # CLI
export VARRD_API_KEY=your-key # Environment variable
---
scan
Free
search
Free
get_hypothesis
Free
balance
Free
reset
Free
research
~20-30c
discover
~20-30c
| Tool | Cost | Description |
|------|------|-------------|
| scan | Free | Scan strategies against live data. What's firing right now? |
| search | Free | Find saved strategies by keyword or natural language. |
| get_hypothesis | Free | Full details on a specific strategy. |
| balance | Free | Check credit balance. |
| reset | Free | Kill a stuck research session. |
| research | ~20-30c | Multi-turn research with VARRD AI. You drive the conversation. |
| discover | ~20-30c | Autonomous edge discovery. VARRD drives. |
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"varrd": {
"augiemazza-varrd": {
"args": [],
"command": "varrd"
}
}
}
}McpServers
{
"augiemazza-varrd": {
"args": [],
"command": "varrd"
}
}
pip install varrd
`
---
Why This Matters
There are things in quantitative testing that are near-invisible to the human eye. Not complex — invisible. The kind of stuff that a PhD statistician catches on instinct after 15 years, that a trader learns the hard way after blowing up twice, that a quant at Citadel takes for granted but never explains because it's just "how things are done."
Things like:
- Why testing 5 RSI thresholds and picking the best one isn't the same as testing 1
- Why a strategy that "beats the market" might actually be behind the market
- Why every formula tweak is a statistical test, whether you think of it that way or not
- Why your out-of-sample validation becomes worthless the moment you use it to make a decision
- Why the number of observations matters in ways that aren't obvious
- Why significance at one horizon says nothing about significance at another
These aren't advanced topics. They're table stakes. And if even one of them is handled wrong, the whole result is unreliable.
VARRD handles all of them. Automatically. Invisibly. You don't configure anything. You don't set penalty parameters. You don't choose which corrections to apply. The system knows what needs to happen at each stage of research and it does it — the same way a quant at a top firm would, except it never forgets a step and it never cuts corners because it's 4pm on a Friday.
You don't need to know what any of this means. That's the point.
---
Quick Start — Python
``python
from varrd import VARRD
v = VARRD() # auto-creates free accountSign in to leave a review
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