Brain API Overview - Gigabrain Docs

One endpoint. Stateless. Ask anything in plain English, get back trade-ready analysis. No sessions to manage, no state to track.

POST /v1/chat

Rate limit: 60 requests per minute. Set your HTTP client timeout to at least 600 seconds. See Auth & Basics for full details.

Get a Trade Setup

Ask The Brain for a trade and get back entry, stop-loss, and targets you can feed straight into your execution logic.

Python
JavaScript
cURL

import requests, json

response = requests.post(
    "https://api.gigabrain.gg/v1/chat",
    headers={"Authorization": "Bearer gb_sk_..."},
    json={
        "message": "Should I long or short ETH right now? Check technicals, funding rates, and macro. Respond as JSON with: direction, entry_price, stop_loss, take_profit_1, take_profit_2, risk_reward_ratio, confidence, reasoning"
    },
    timeout=600
)

setup = json.loads(response.json()["content"])
print(f"{setup['direction']} ETH @ {setup['entry_price']}")
print(f"Stop: {setup['stop_loss']} | TP1: {setup['take_profit_1']} | TP2: {setup['take_profit_2']}")
print(f"R:R {setup['risk_reward_ratio']} | Confidence: {setup['confidence']}/10")

const res = await fetch("https://api.gigabrain.gg/v1/chat", {
  method: "POST",
  headers: {
    Authorization: "Bearer gb_sk_...",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    message: "Should I long or short ETH right now? Check technicals, funding rates, and macro. Respond as JSON with: direction, entry_price, stop_loss, take_profit_1, take_profit_2, risk_reward_ratio, confidence, reasoning",
  }),
  signal: AbortSignal.timeout(600000),
});

const setup = JSON.parse((await res.json()).content);
console.log(`${setup.direction} ETH @ ${setup.entry_price}`);
console.log(`Stop: ${setup.stop_loss} | TP1: ${setup.take_profit_1} | TP2: ${setup.take_profit_2}`);
console.log(`R:R ${setup.risk_reward_ratio} | Confidence: ${setup.confidence}/10`);

curl -X POST https://api.gigabrain.gg/v1/chat \
  -H "Authorization: Bearer gb_sk_..." \
  -H "Content-Type: application/json" \
  -d '{"message": "Should I long or short ETH right now? Check technicals, funding rates, and macro. Respond as JSON with: direction, entry_price, stop_loss, take_profit_1, take_profit_2, risk_reward_ratio, confidence, reasoning"}'

The response comes back in the content field (not message). Add “Respond as JSON with:” to any query and specify the fields you want - the content field will contain parseable JSON instead of markdown.

Find Squeeze Setups

Scan for tokens where positioning is extreme and a liquidation cascade could trigger a move.

Python
JavaScript

response = requests.post(
    "https://api.gigabrain.gg/v1/chat",
    headers={"Authorization": "Bearer gb_sk_..."},
    json={
        "message": "Find tokens with extreme funding rates and crowded positioning that could squeeze. Respond as JSON array with: symbol, funding_rate, open_interest, long_short_ratio, squeeze_direction, liquidation_risk, catalyst"
    },
    timeout=600
)

squeezes = json.loads(response.json()["content"])
for s in squeezes:
    print(f"{s['symbol']}: {s['squeeze_direction']} squeeze, funding {s['funding_rate']}")

const res = await fetch("https://api.gigabrain.gg/v1/chat", {
  method: "POST",
  headers: {
    Authorization: "Bearer gb_sk_...",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    message: "Find tokens with extreme funding rates and crowded positioning that could squeeze. Respond as JSON array with: symbol, funding_rate, open_interest, long_short_ratio, squeeze_direction, liquidation_risk, catalyst",
  }),
  signal: AbortSignal.timeout(600000),
});

const squeezes = JSON.parse((await res.json()).content);
squeezes.forEach((s) =>
  console.log(`${s.symbol}: ${s.squeeze_direction} squeeze, funding ${s.funding_rate}`)
);

Screen for Macro Risk

Check if macro conditions support risk-on or if you should be reducing exposure.

Python
JavaScript

response = requests.post(
    "https://api.gigabrain.gg/v1/chat",
    headers={"Authorization": "Bearer gb_sk_..."},
    json={
        "message": "What's the current macro risk regime for crypto? Factor in DXY, yields, VIX, and equities. Respond as JSON with: risk_regime, dxy_trend, vix_level, yield_curve_signal, equity_correlation, recommended_exposure, reasoning"
    },
    timeout=600
)

macro = json.loads(response.json()["content"])
print(f"Regime: {macro['risk_regime']} | Exposure: {macro['recommended_exposure']}")

const res = await fetch("https://api.gigabrain.gg/v1/chat", {
  method: "POST",
  headers: {
    Authorization: "Bearer gb_sk_...",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    message: "What's the current macro risk regime for crypto? Factor in DXY, yields, VIX, and equities. Respond as JSON with: risk_regime, dxy_trend, vix_level, yield_curve_signal, equity_correlation, recommended_exposure, reasoning",
  }),
  signal: AbortSignal.timeout(600000),
});

const macro = JSON.parse((await res.json()).content);
console.log(`Regime: ${macro.risk_regime} | Exposure: ${macro.recommended_exposure}`);

Spot Early Narratives

Find narratives gaining momentum before they go mainstream.

Python
JavaScript

response = requests.post(
    "https://api.gigabrain.gg/v1/chat",
    headers={"Authorization": "Bearer gb_sk_..."},
    json={
        "message": "What crypto narratives are gaining momentum right now? Rank by strength. Respond as JSON array with: narrative, momentum_score, top_tokens, sentiment, key_catalyst, risk_level"
    },
    timeout=600
)

narratives = json.loads(response.json()["content"])
for n in narratives[:5]:
    print(f"{n['narrative']} (momentum: {n['momentum_score']}/100) - {', '.join(n['top_tokens'])}")

const res = await fetch("https://api.gigabrain.gg/v1/chat", {
  method: "POST",
  headers: {
    Authorization: "Bearer gb_sk_...",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    message: "What crypto narratives are gaining momentum right now? Rank by strength. Respond as JSON array with: narrative, momentum_score, top_tokens, sentiment, key_catalyst, risk_level",
  }),
  signal: AbortSignal.timeout(600000),
});

const narratives = JSON.parse((await res.json()).content);
narratives.slice(0, 5).forEach((n) =>
  console.log(`${n.narrative} (momentum: ${n.momentum_score}/100) - ${n.top_tokens.join(", ")}`)
);

SuperAgents API

Want always-on agents instead? Launch, manage, and chat with autonomous trading agents programmatically.

Gigabrain provides market intelligence tools, not financial advice. Always do your own research before trading. See the Risk Disclosure.

Getting Started

Brain

SuperAgents

​Get a Trade Setup

​Find Squeeze Setups

​Screen for Macro Risk

​Spot Early Narratives

SuperAgents API

Get a Trade Setup

Find Squeeze Setups

Screen for Macro Risk

Spot Early Narratives