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Accède aux données financières via Financial Modeling Prep (FMP) — cours boursiers, profil d'entreprise, bilans, ratios, actualités, screener, indices, crypto et forex.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | fmp |
| category | finance |
| description | Accède aux données financières via Financial Modeling Prep (FMP) — cours boursiers, profil d'entreprise, bilans, ratios, actualités, screener, indices, crypto et forex. |
| tags | ["finance","bourse","actions","crypto","forex","analyse-fondamentale","marché"] |
| requires | {"env_vars":["FMP_API_KEY"]} |
Accès complet aux données financières via l'API Financial Modeling Prep (endpoints stables v2025+).
Base URL : https://financialmodelingprep.com/stable
Auth : paramètre apikey dans chaque requête (valeur : variable d'env FMP_API_KEY)
🔑 Crée ton compte et récupère ta clef sur financialmodelingprep.com
Ajoute ta clef dans ~/.hermes/.env :
FMP_API_KEY=ta_clef_ici
import os, urllib.request, json
API = "https://financialmodelingprep.com/stable"
KEY = os.environ["FMP_API_KEY"]
def fmp(path, **params):
params["apikey"] = KEY
qs = "&".join(f"{k}={v}" for k, v in params.items())
url = f"{API}/{path}?{qs}"
return json.loads(urllib.request.urlopen(url).read())
prix = fmp("quote", symbol="AAPL")
print(f"{prix[0]['symbol']}: ${prix[0]['price']} ({prix[0]['changesPercentage']:+.2f}%)")
p = fmp("profile", symbol="TSLA")[0]
print(f"{p['companyName']} — {p['sector']} — Cap: ${p['marketCap']:,.0f}")
print(f"CEO: {p['ceo']} | {p['description'][:200]}")
income = fmp("income-statement", symbol="MSFT", period="quarter", limit=4)
for q in income:
print(f"{q['date']}: Revenue ${q['revenue']:,.0f} | Net ${q['netIncome']:,.0f}")
r = fmp("ratios", symbol="AAPL", period="annual", limit=1)[0]
print(f"PE: {r['priceEarningsRatio']:.1f} | ROE: {r['returnOnEquity']*100:.1f}%")
print(f"Marge nette: {r['netProfitMargin']*100:.1f}% | Dividende: {r['dividendYield']*100:.2f}%")
results = fmp("stock-screener",
marketCapMoreThan=10000000000,
peRatioLowerThan=20,
sector="Technology",
country="US",
limit=20)
for s in results:
print(f"{s['symbol']} — PE: {s['peRatio']:.1f} — Cap: ${s['marketCap']:,.0f}")
indices = fmp("quotes/index")
for idx in indices:
if idx['symbol'] in ['^GSPC', '^IXIC', '^DJI', '^FCHI']:
print(f"{idx['name']}: {idx['price']:,.2f} ({idx['changesPercentage']:+.2f}%)")
btc = fmp("quote", symbol="BTCUSD")[0]
eur = fmp("quote", symbol="EURUSD")[0]
print(f"BTC: ${btc['price']:,.2f} | EUR/USD: {eur['price']:.4f}")
news = fmp("stock-news", tickers="AAPL,MSFT", limit=5)
for n in news:
print(f"[{n['publishedDate'][:10]}] {n['title']}")
gainers = fmp("stock_market/gainers")
for s in gainers[:5]:
print(f"{s['ticker']}: +{s['changesPercentage']:.1f}%")
dcf = fmp("discounted-cash-flow", symbol="AAPL")[0]
print(f"DCF estimé: ${dcf['dcf']:.2f} vs cours actuel: ${dcf['stockPrice']:.2f}")
| Type | Symboles |
|---|---|
| Indices | ^GSPC (S&P500), ^IXIC (Nasdaq), ^DJI (Dow Jones), ^FCHI (CAC40) |
| Crypto | BTCUSD, ETHUSD, SOLUSD |
| Forex | EURUSD, GBPUSD, USDJPY |
results = fmp("search", query="LVMH", limit=5)
for r in results:
print(f"{r['symbol']} — {r['name']} ({r['exchangeShortName']})")
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