SentiSense Logo
SentiSense
SentiSense Logo
SentiSense
Sign InGet Free API Key
←Back to the notebook

Fear and Greed Index API: Market Mood for Python, Node and AI Agents

A fear and greed index API with a documented schema. SentiSense Market Mood returns a 0-100 fear-to-greed score for the US stock market, its phase, six signal components, sector scores and trading-day history. One free key, then curl, Python, Node, a CLI, an MCP tool or an agent skill.

SentiSense Team
SentiSense Team
September 25, 2026 · 7 min read

SentiSense Market Mood is a fear and greed index API: GET https://app.sentisense.ai/api/v2/market-mood returns a 0-100 fear-to-greed score for the US stock market, its phase, the six signals behind it, per-sector scores and daily history, with a documented schema and a free API key. Market Mood is our own index, built from our own signals. "Fear and greed index" is the category it belongs to.

Every example below ran against the live API on 2026-09-25 with a free key.

Is there a fear and greed index API?

Yes. Market Mood is served two ways with one key:

  • GET /api/v2/market-mood?days=180: the full view. Composite score, phase, weekly change, the six signals, daily history over the requested window and a score for each of the 11 GICS sectors.
  • GET /api/v1/indexes/market-mood and /api/v1/indexes/market-mood/history?days=180: the same headline number in the shared Indexes API envelope, alongside the Fed Sentiment and AI Sentiment indexes.

Both are available on every tier with identical payloads. Requests need an API key and count against the monthly quota.

What does the fear and greed index API return?

curl -H "X-SentiSense-API-Key: $SENTISENSE_API_KEY" \
  "https://app.sentisense.ai/api/v2/market-mood?days=30"

Output on 2026-09-25, trimmed to one history point and two sectors:

{
  "market": {
    "currentScore": 59.13914353924022,
    "phase": "Optimism",
    "weeklyChange": 22.4,
    "signals": [
      { "key": "social_sentiment", "label": "Social Sentiment", "value": 53.19, "change": 0 },
      { "key": "market_direction", "label": "Market Direction", "value": 64.57, "change": 33.5 },
      { "key": "fear_gauge", "label": "Risk Appetite", "value": 98.59, "change": 2.8 },
      { "key": "social_momentum", "label": "Social Momentum", "value": 48.35, "change": 48.4 },
      { "key": "spy_trend", "label": "S&P 500 Trend", "value": 31.11, "change": 17.8 },
      { "key": "options_flow", "label": "Options Flow", "value": 56.99, "change": 57.0 }
    ],
    "history": [
      { "date": "2026-09-25", "timestamp": 1790308800000, "score": 59.13914353924022,
        "socialSentiment": 53.19, "marketDirection": 64.57, "fearGauge": 98.59,
        "socialMomentum": 48.35, "spyTrend": 31.11, "optionsFlow": 56.99 }
    ]
  },
  "sectors": {
    "Information Technology": { "currentScore": 66.5663145832018, "phase": "Optimism", "weeklyChange": 16.6 },
    "Real Estate": { "currentScore": 39.4699315952405, "phase": "Anxiety", "weeklyChange": 7.4 }
  }
}

How to read it:

  • currentScore is 0-100, higher is greedier. phase maps the score onto seven bands: Extreme Fear (0-15), Fear (16-30), Anxiety (31-45), Neutral (46-55), Optimism (56-70), Greed (71-85), Extreme Greed (86-100).
  • weeklyChange and each signal's change are the move over the last five trading days.
  • signals share the composite's 0-100 scale. Match on key, not array position; only the signals present in the latest reading are listed. fear_gauge is labeled Risk Appetite because it is an inverse volatility read: high means calm, risk-on.
  • history has one point per weekday and no weekend rows (days=30 returned 21 points). The last point's date is the reading's freshness.
  • sectors is keyed by GICS sector name, each with its own score, phase and weekly change.

Field-by-field reference: the Market Mood API page.

Stock market fear and greed index in Python

pip install sentisense
export SENTISENSE_API_KEY=ss_live_YOUR_KEY

Today's reading with the signal breakdown:

import os
from sentisense import SentiSenseClient

client = SentiSenseClient(api_key=os.environ["SENTISENSE_API_KEY"])
mood = client.get_market_mood(days=30)

m = mood["market"]
latest = m["history"][-1]
print(f"Market Mood {m['currentScore']:.1f} ({m['phase']}) as of {latest['date']}, "
      f"weekly change {m['weeklyChange']:+.1f}")
for s in m["signals"]:
    print(f"  {s['label']:17} {s['value']:5.1f}  (week {s['change']:+.1f})")
print(f"{len(m['history'])} trading days in the window, {m['history'][0]['date']} to {latest['date']}")

Market Mood 59.1 (Optimism) as of 2026-09-25, weekly change +22.4
  Social Sentiment   53.2  (week +0.0)
  Market Direction   64.6  (week +33.5)
  Risk Appetite      98.6  (week +2.8)
  Social Momentum    48.4  (week +48.4)
  S&P 500 Trend      31.1  (week +17.8)
  Options Flow       57.0  (week +57.0)
21 trading days in the window, 2026-08-28 to 2026-09-25

The Indexes route returns the plain date-and-value series. This script lists the days the index crossed into a different band:

BANDS = [(15, "Extreme Fear"), (30, "Fear"), (45, "Anxiety"), (55, "Neutral"),
         (70, "Optimism"), (85, "Greed"), (100, "Extreme Greed")]
band = lambda v: next(label for edge, label in BANDS if v <= edge)

hist = client.get_index_history("market-mood", days=180).history
print(f"{len(hist)} trading days, {hist[0].date} to {hist[-1].date}")

changes = [(a, b) for a, b in zip(hist, hist[1:]) if band(a.value) != band(b.value)]
print(f"{len(changes)} band changes; the last five:")
for a, b in changes[-5:]:
    print(f"  {b.date}  {band(a.value)} -> {band(b.value)}  ({a.value:.1f} -> {b.value:.1f})")

129 trading days, 2026-03-31 to 2026-09-25
39 band changes; the last five:
  2026-09-08  Neutral -> Anxiety  (49.3 -> 42.8)
  2026-09-16  Anxiety -> Fear  (31.8 -> 28.5)
  2026-09-17  Fear -> Anxiety  (28.5 -> 39.3)
  2026-09-21  Anxiety -> Neutral  (36.8 -> 49.5)
  2026-09-25  Neutral -> Optimism  (54.0 -> 59.1)

client.get_index("market-mood") returns the latest reading in the same envelope; its constituents, basketSize, coverage and totalMentions are None, because a composite has no constituents by construction.

Fear and greed index in Node

npm install sentisense

import SentiSense from "sentisense";

const client = new SentiSense({ apiKey: process.env.SENTISENSE_API_KEY });

const { market, sectors } = await client.marketMood.get();
console.log(`Market Mood ${market.currentScore.toFixed(1)} (${market.phase}), weekly ${market.weeklyChange > 0 ? "+" : ""}${market.weeklyChange}`);
const ranked = Object.entries(sectors).sort((a, b) => b[1].currentScore - a[1].currentScore);
for (const [name, s] of ranked.slice(0, 3)) console.log(`  ${name}: ${s.currentScore.toFixed(1)} (${s.phase})`);

const { history } = await client.indexes.history("market-mood", 30);
console.log(`${history.length} trading days, last ${history.at(-1).date} = ${history.at(-1).value.toFixed(1)}`);

Market Mood 59.1 (Optimism), weekly +22.4
  Information Technology: 66.6 (Optimism)
  Health Care: 62.6 (Optimism)
  Industrials: 56.9 (Optimism)
21 trading days, last 2026-09-25 = 59.1

Fear and greed index for AI agents

An agent reads the same series three ways, with no script.

MCP connector. Add https://app.sentisense.ai/mcp to Claude, ChatGPT or Grok as a custom connector and sign in; no key to paste. From a terminal:

# Claude Code
claude mcp add sentisense -- npx -y mcp-remote@0.1.38 https://app.sentisense.ai/mcp

# Codex
codex mcp add sentisense --url https://app.sentisense.ai/mcp
codex mcp login sentisense

The get_market_mood tool takes no arguments and returns the score and phase, the weekly change, the six signals with band labels, and the hottest and coolest sectors, with a note that the reading is the latest analytical batch, not a real-time quote. Per-host setup: the MCP connector page.

CLI. Any agent with a shell can run the official CLI with nothing installed:

npx -y sentisense mood          # terminal layout: score, signals, a 60-day sparkline, the sector table
npx -y sentisense mood --json   # the exact /api/v2/market-mood response

Skills. The SentiSense skills are markdown playbooks a coding agent reads. The sentisense API reference, stock-sentiment, stock-market-dashboard, last-30-days-in-markets and market-heatmap skills all read Market Mood.

# Claude Code
claude plugin marketplace add SentiSenseApp/skills
claude plugin install sentisense@sentisense

# Cursor, Codex, Gemini and other coding agents
npx skills add SentiSenseApp/skills

# OpenClaw
openclaw plugins install clawhub:@sentisenseapp/stock-analysis

The CLI and the skills read the key from SENTISENSE_API_KEY. Without an installer, point the agent at sentisense.ai/skill.md, the whole API reference in one file.

How often does it update, and what does it cost?

Market Mood is recomputed on US trading days, several times a day, with the last pass in the evening Eastern time, so a day's reading settles after the close. It is a nowcast of how the market feels, not a forecast and not a live tick.

A free key covers everything on this page: 1,000 requests a month at up to 30 a minute, with the full payload. PRO removes the monthly cap and raises the rate limit to 300 a minute, which matters once a dashboard polls sectors and history on a schedule. The same index is on the live page at app.sentisense.ai/indexes/market-mood.

Related reading

Ready to run it? Get a free API key → and paste it into the export line above.

SentiSense provides market information and sentiment analysis for informational and educational purposes only. Market Mood is derived from AI-analyzed data and should not be relied upon for investment decisions. It is not investment advice.