Financial Modeling Prep API for stocks, fundamentals, SEC filings, institutional holdings (13F), and congressional trading.

MITAuto-check: notesBusiness, Finance & HR

Install Fmp API

skills CLI
$ npx skills add majiayu000/claude-skill-registry --skill fmp-api -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install majiayu000/claude-skill-registry fmp-api --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/api/fmp-api-adaptationio-skrillz-2 .claude/skills/fmp-api && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
fmp-api
GitHub stars
666
Used in
1 other repo
Token cost
~3.3k tokens
SKILL.md length
459 words
Files
2
Skills in repo
971
Repo updated
First seen
Licence
MIT

At a glance

Financial Modeling Prep API for stocks, fundamentals, SEC filings, institutional holdings (13F), and congressional trading.

  • Works in 6 steps: Pre-computed DCF - Ready-to-use valuations → Congressional Trading - Senate/House… → 13F Filings - Institutional holdings… → …
  • Fetching financial statements
  • SKILL.md covers Quick Start, API Endpoints Reference, Rate Limits and Common Tasks, plus 4 more sections
  • Reaches financialmodelingprep.com; needs API_KEY and FMP_API_KEY

What it does

Fmp API is an agent skill from majiayu000/claude-skill-registry. Financial Modeling Prep API for stocks, fundamentals, SEC filings, institutional holdings (13F), and congressional trading. Use when fetching financial statements, ratios, DCF valuations, insider/institutional ownership, or screening stocks.

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

It sits in Business, Finance & HR, covering Financial modeling, Financial analysis and Trading and backtesting. It works with SEC EDGAR. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.

When your agent uses it

  • Fetching financial statements
  • Insider/institutional ownership
  • Screening stocks

Example prompts

  • “/fmp-api”

Requirements

  • Python 3
  • A credential in FMP_API_KEY
  • A credential in API_KEY

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Pre-computed DCF - Ready-to-use valuations
  2. Congressional Trading - Senate/House STOCK Act data
  3. 13F Filings - Institutional holdings analysis
  4. Standardized Financials - Normalized line items
  5. Company Outlook - All data in one endpoint
  6. Rating System - Proprietary company ratings

What it can do on your machine

Read from SKILL.md and the folder at commit 000116a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are python and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • financialmodelingprep.com

    Also links to:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • API_KEY
    • FMP_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Fmp API loads about 3.3k tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 459 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~62
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:18
    # Or in .env file

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 000116a, republished under its MIT licence (© majiayu000). 459 words, ~3,314 tokens.

Download SKILL.mdSave it as .claude/skills/fmp-api/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
fmp-api
description
Financial Modeling Prep API for stocks, fundamentals, SEC filings, institutional holdings (13F), and congressional trading. Use when fetching financial statements, ratios, DCF valuations, insider/institutional ownership, or screening stocks.
version
1.0.0

Financial Modeling Prep (FMP) API Integration

Comprehensive financial data API specializing in fundamental analysis, SEC filings, institutional holdings (13F), congressional trading data, and pre-computed valuations.

Quick Start

Authentication
bash
# Environment variable (recommended)
export FMP_API_KEY="your_api_key"

# Or in .env file
FMP_API_KEY=your_api_key
Basic Usage (Python)
python
import requests
import os

API_KEY = os.getenv("FMP_API_KEY")
BASE_URL = "https://financialmodelingprep.com/stable"

def get_quote(symbol: str) -> dict:
    """Get real-time quote for a symbol."""
    response = requests.get(
        f"{BASE_URL}/quote",
        params={"symbol": symbol, "apikey": API_KEY}
    )
    data = response.json()
    return data[0] if data else {}

# Example
quote = get_quote("AAPL")
print(f"AAPL: ${quote['price']:.2f} ({quote['changePercentage']:+.2f}%)")
Important: New Endpoint Format

FMP migrated to /stable/ endpoints. Legacy /api/v3/ endpoints require existing subscriptions.

python
# NEW format (use this)
BASE_URL = "https://financialmodelingprep.com/stable"

# OLD format (legacy only)
# BASE_URL = "https://financialmodelingprep.com/api/v3"

API Endpoints Reference

Stock Quotes & Prices
EndpointDescriptionFree
/quoteReal-time quote✅
/quote-shortQuick price✅
/historical-price-eod/fullHistorical EOD✅
/historical-price-intradayIntraday prices⚠️ Paid
/pre-post-market-quoteExtended hours⚠️ Paid
Financial Statements
EndpointDescriptionFree
/income-statementIncome statement✅
/balance-sheet-statementBalance sheet✅
/cash-flow-statementCash flow✅
/income-statement-growthIncome growth✅
/key-metricsKey metrics✅
/financial-ratiosFinancial ratios✅
/enterprise-valuesEnterprise value✅
Valuations & Analysis
EndpointDescriptionFree
/discounted-cash-flowDCF valuation✅
/historical-discounted-cash-flowHistorical DCF✅
/ratingCompany rating✅
/historical-ratingRating history✅
/company-outlookFull company data✅
Institutional & Insider Data
EndpointDescriptionFree
/institutional-holderInstitutional owners⚠️ Paid
/mutual-fund-holderMutual fund owners⚠️ Paid
/insider-tradingInsider transactions⚠️ Paid
/form-13f13F filings⚠️ Paid
/senate-tradingSenate trades⚠️ Paid
/house-tradingHouse trades⚠️ Paid
Screening & Discovery
EndpointDescriptionFree
/stock-screenerScreen stocks⚠️ Paid
/stock-gradeStock grades✅
/searchSearch symbols✅
/search-nameSearch by name✅
/profileCompany profile✅
Calendars & Events
EndpointDescriptionFree
/earnings-calendarEarnings dates✅
/ipo-calendarIPO dates✅
/stock-dividend-calendarDividends✅
/stock-split-calendarStock splits✅
/economic-calendarEconomic events✅
SEC Filings
EndpointDescriptionFree
/sec-filingsAll SEC filings✅
/rss-feed-sec-filingsSEC RSS feed✅

Rate Limits

TierCalls/DayCalls/MinPrice
Free250N/A$0
StarterUnlimited300$22/mo
PremiumUnlimited750$59/mo
UltimateUnlimited3,000$149/mo

Free tier limitations:

  • ~100 sample symbols (AAPL, TSLA, AMZN, etc.)
  • End-of-day data only
  • 500MB bandwidth (30-day rolling)

Common Tasks

Task: Get Financial Statements
python
def get_financials(symbol: str, period: str = "annual") -> dict:
    """Get comprehensive financial statements."""

    income = requests.get(
        f"{BASE_URL}/income-statement",
        params={"symbol": symbol, "period": period, "apikey": API_KEY}
    ).json()

    balance = requests.get(
        f"{BASE_URL}/balance-sheet-statement",
        params={"symbol": symbol, "period": period, "apikey": API_KEY}
    ).json()

    cashflow = requests.get(
        f"{BASE_URL}/cash-flow-statement",
        params={"symbol": symbol, "period": period, "apikey": API_KEY}
    ).json()

    return {
        "income_statement": income[0] if income else {},
        "balance_sheet": balance[0] if balance else {},
        "cash_flow": cashflow[0] if cashflow else {}
    }

# Example
financials = get_financials("AAPL")
print(f"Revenue: ${financials['income_statement'].get('revenue', 0):,.0f}")
Task: Get Key Metrics & Ratios
python
def get_key_metrics(symbol: str) -> dict:
    """Get important financial metrics."""

    metrics = requests.get(
        f"{BASE_URL}/key-metrics",
        params={"symbol": symbol, "period": "annual", "apikey": API_KEY}
    ).json()

    ratios = requests.get(
        f"{BASE_URL}/financial-ratios",
        params={"symbol": symbol, "period": "annual", "apikey": API_KEY}
    ).json()

    latest_metrics = metrics[0] if metrics else {}
    latest_ratios = ratios[0] if ratios else {}

    return {
        "market_cap": latest_metrics.get("marketCap"),
        "pe_ratio": latest_ratios.get("priceEarningsRatio"),
        "pb_ratio": latest_ratios.get("priceToBookRatio"),
        "roe": latest_ratios.get("returnOnEquity"),
        "roa": latest_ratios.get("returnOnAssets"),
        "debt_equity": latest_ratios.get("debtEquityRatio"),
        "current_ratio": latest_ratios.get("currentRatio"),
        "gross_margin": latest_ratios.get("grossProfitMargin"),
        "operating_margin": latest_ratios.get("operatingProfitMargin"),
        "net_margin": latest_ratios.get("netProfitMargin"),
        "dividend_yield": latest_ratios.get("dividendYield"),
        "payout_ratio": latest_ratios.get("payoutRatio")
    }
Task: Get DCF Valuation
python
def get_dcf_valuation(symbol: str) -> dict:
    """Get pre-computed DCF valuation."""
    response = requests.get(
        f"{BASE_URL}/discounted-cash-flow",
        params={"symbol": symbol, "apikey": API_KEY}
    )
    data = response.json()

    if data:
        dcf = data[0]
        return {
            "symbol": dcf.get("symbol"),
            "dcf_value": dcf.get("dcf"),
            "stock_price": dcf.get("stockPrice"),
            "upside": ((dcf.get("dcf", 0) / dcf.get("stockPrice", 1)) - 1) * 100
        }
    return {}

# Example
dcf = get_dcf_valuation("AAPL")
print(f"DCF Value: ${dcf['dcf_value']:.2f} ({dcf['upside']:+.1f}% upside)")
Task: Get Company Profile
python
def get_company_profile(symbol: str) -> dict:
    """Get comprehensive company information."""
    response = requests.get(
        f"{BASE_URL}/profile",
        params={"symbol": symbol, "apikey": API_KEY}
    )
    data = response.json()

    if data:
        profile = data[0]
        return {
            "name": profile.get("companyName"),
            "symbol": profile.get("symbol"),
            "sector": profile.get("sector"),
            "industry": profile.get("industry"),
            "market_cap": profile.get("mktCap"),
            "price": profile.get("price"),
            "beta": profile.get("beta"),
            "ceo": profile.get("ceo"),
            "website": profile.get("website"),
            "description": profile.get("description"),
            "employees": profile.get("fullTimeEmployees"),
            "exchange": profile.get("exchange"),
            "ipo_date": profile.get("ipoDate")
        }
    return {}
Task: Get Earnings Calendar
python
def get_earnings_calendar(from_date: str, to_date: str) -> list:
    """Get upcoming earnings announcements."""
    response = requests.get(
        f"{BASE_URL}/earnings-calendar",
        params={
            "from": from_date,
            "to": to_date,
            "apikey": API_KEY
        }
    )
    return response.json()

# Example
from datetime import datetime, timedelta
today = datetime.now()
next_week = today + timedelta(days=7)

earnings = get_earnings_calendar(
    today.strftime("%Y-%m-%d"),
    next_week.strftime("%Y-%m-%d")
)

for e in earnings[:5]:
    print(f"{e['symbol']}: {e['date']} ({e.get('time', 'N/A')})")
Task: Get Historical Prices
python
def get_historical_prices(symbol: str, start: str = None, end: str = None) -> list:
    """Get historical end-of-day prices."""
    params = {"symbol": symbol, "apikey": API_KEY}
    if start:
        params["from"] = start
    if end:
        params["to"] = end

    response = requests.get(
        f"{BASE_URL}/historical-price-eod/full",
        params=params
    )
    data = response.json()
    return data.get("historical", [])

# Example
prices = get_historical_prices("AAPL", "2025-01-01", "2025-12-01")
print(f"Got {len(prices)} days of data")
Task: Search for Companies
python
def search_companies(query: str, limit: int = 10) -> list:
    """Search for companies by name or symbol."""
    response = requests.get(
        f"{BASE_URL}/search",
        params={
            "query": query,
            "limit": limit,
            "apikey": API_KEY
        }
    )
    return response.json()

# Example
results = search_companies("Apple")
for r in results[:5]:
    print(f"{r['symbol']}: {r['name']} ({r['exchangeShortName']})")
Show full SKILL.md (185 more words)Show less
Task: Get SEC Filings
python
def get_sec_filings(symbol: str, filing_type: str = None) -> list:
    """Get SEC filings for a company."""
    params = {"symbol": symbol, "apikey": API_KEY}
    if filing_type:
        params["type"] = filing_type  # 10-K, 10-Q, 8-K, etc.

    response = requests.get(
        f"{BASE_URL}/sec-filings",
        params=params
    )
    return response.json()

# Example: Get 10-K filings
filings = get_sec_filings("AAPL", "10-K")
for f in filings[:3]:
    print(f"{f['type']}: {f['fillingDate']} - {f['link']}")

Error Handling

python
def safe_api_call(endpoint: str, params: dict) -> dict:
    """Make API call with error handling."""
    params["apikey"] = API_KEY

    try:
        response = requests.get(f"{BASE_URL}/{endpoint}", params=params)
        data = response.json()

        # Check for error messages
        if isinstance(data, dict) and "Error Message" in data:
            print(f"API Error: {data['Error Message']}")
            return {}

        # Check for empty response
        if not data:
            print(f"No data returned for {endpoint}")
            return {}

        return data

    except requests.exceptions.RequestException as e:
        print(f"Request error: {e}")
        return {}
    except ValueError as e:
        print(f"JSON decode error: {e}")
        return {}

Free vs Paid Features

Free Tier Includes
  • 250 API calls/day
  • ~100 sample symbols
  • Financial statements
  • Key metrics & ratios
  • DCF valuations
  • Company profiles
  • Earnings calendar
  • SEC filings list
  • Basic historical data
Paid Features (Starter+)
  • Unlimited symbols
  • Intraday data
  • Stock screener
  • International stocks
  • Institutional holders
  • Mutual fund holders
  • ETF holdings breakdown
Paid Features (Premium+)
  • Higher rate limits
  • 13F filings
  • Insider trading
  • Congressional trading (Senate/House)
  • Analyst estimates
  • Earnings transcripts
  • Extended hours data

Unique FMP Features

  1. Pre-computed DCF - Ready-to-use valuations
  2. Congressional Trading - Senate/House STOCK Act data
  3. 13F Filings - Institutional holdings analysis
  4. Standardized Financials - Normalized line items
  5. Company Outlook - All data in one endpoint
  6. Rating System - Proprietary company ratings

Best Practices

  1. Use stable endpoints - /stable/ not /api/v3/
  2. Cache static data - Profiles, historical data
  3. Monitor daily limits - 250 calls goes fast
  4. Batch symbol lookups - Where supported
  5. Store financials - They only update quarterly
  6. Use company-outlook - Single call for all data

Installation

python
# Recommended Python wrapper
pip install --upgrade FinancialModelingPrep-Python

# Basic usage
from fmp_python.fmp import FMP
fmp = FMP(api_key="your_api_key")
profile = fmp.get_company_profile("AAPL")
  • finnhub-api - Real-time quotes and news
  • twelvedata-api - Technical indicators
  • alphavantage-api - Economic indicators

References

© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/api/fmp-api-adaptationio-skrillz-2 of majiayu000/claude-skill-registry.

  • SKILL.md
  • metadata.json

Open the folder on GitHubat commit 000116a

Used in 1 other repository

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Fmp API next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Dcf ModelWind-Alice/AliceMarket1283 repos~12kAutomated safety check: PassNone
Edgartoolsagent-skills-hub/agent-skills-hub1112 repos~1.4kAutomated safety check: PassMIT
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Works with

Questions about Fmp API

What does Fmp API do?

Financial Modeling Prep API for stocks, fundamentals, SEC filings, institutional holdings (13F), and congressional trading. Fmp API is an agent skill from majiayu000/claude-skill-registry. Financial Modeling Prep API for stocks, fundamentals, SEC filings, institutional holdings (13F), and congressional trading.

When should I use Fmp API?

Fmp API fits situations like: fetching financial statements; insider/institutional ownership; screening stocks.

How do I install Fmp API in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill fmp-api -a claude-code`. Or copy the skill folder (skills/api/fmp-api-adaptationio-skrillz-2 in majiayu000/claude-skill-registry) into .claude/skills/fmp-api in your project. Claude Code loads it when a task matches its description.

How do I install Fmp API in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill fmp-api -a codex`. Or copy the skill folder (skills/api/fmp-api-adaptationio-skrillz-2 in majiayu000/claude-skill-registry) into .agents/skills/fmp-api in your project. Codex loads it when a task matches its description.

Can I use Fmp API in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill fmp-api -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fmp-api, .gemini/skills/fmp-api, .github/skills/fmp-api and .opencode/skills/fmp-api in your project.

What does Fmp API need to run?

Going by SKILL.md and its folder, Fmp API needs credentials named API_KEY and FMP_API_KEY. Our summary lists: Python 3; A credential in FMP_API_KEY; A credential in API_KEY.

Does Fmp API access the network?

SKILL.md names 2 domains. In commands or code: financialmodelingprep.com; the agent is likely to contact it when it follows the instructions. As links in the text: github.com. This is read from the text; nothing was executed.

Is Fmp API safe to install?

Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Fmp API use?

Fmp API is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Fmp API use?

About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Fmp API?

Skills that share tags, products or a category with Fmp API: Fintool (second-state/fintool, 316 stars), Money Finance (iamzifei/show-me-the-money, 1k stars), Dcf Model (Wind-Alice/AliceMarket, 128 stars) and Edgartools (agent-skills-hub/agent-skills-hub, 111 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fmp API?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 971 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.