POST /v1/feed

Overview

Retrieve a structured feed of company documents, earnings reports, news, press releases, and other financial content. The endpoint returns organized updates with citations and key highlights.

Request

tickers

array

required

Array of stock ticker symbols to retrieve feeds for (e.g., ["DUOL", "TSLA"])

doc_types

array

Filter by document types. If omitted, returns all types.Available types:

10-K - Annual reports
10-Q - Quarterly reports
8-K - Current reports (material events)
EARNINGS_CALL - Earnings call transcripts
NEWS - News articles
PRESS_RELEASE - Company press releases
PRESENTATION - Company presentations

start_date

string

Filter documents from this date forward (ISO 8601 format: YYYY-MM-DD)

end_date

string

Filter documents up to this date (ISO 8601 format: YYYY-MM-DD)

limit

number

default:50

Maximum number of feed items to return (1-100)

Request Example

curl -X POST https://api.fintool.com/v1/feed \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "tickers": ["DUOL"],
    "doc_types": ["EARNINGS_CALL", "8-K", "NEWS"],
    "start_date": "2025-10-01",
    "limit": 10
  }'

Response

items

array

Array of feed items sorted by date (newest first)

Show Feed Item Object

ticker

string

Stock ticker symbol

company_name

string

Full company name

title

string

Title of the feed item

date

string

Publication date (ISO 8601 format)

doc_type

string

Document type (10-K, 8-K, EARNINGS_CALL, NEWS, etc.)

Response Example

{
  "items": [
    {
      "ticker": "DUOL",
      "company_name": "Duolingo",
      "title": "Duolingo Reports Strong Q3 2025 and Prioritizes Long-Term User Growth",
      "date": "2025-11-05T14:30:00Z",
      "doc_type": "EARNINGS_CALL",
      "categories": ["Earnings", "New Projects/Investments", "Guidance Update"],
      "stock_change": {
        "percentage": -0.79,
        "direction": "down"
      },
      "sentiment": "positive",
      "highlights": [
        {
          "text": "Duolingo achieved strong Q3 2025 results, reporting 36% year-over-year daily active user (DAU) growth and guiding to nearly $1.2 billion in bookings for the year, a 33% increase, with an adjusted EBITDA margin of 29%.",
          "citations": [
            {
              "source": "Earnings Transcript",
              "chunk_id": "duol_q3_2025_earnings_001"
            }
          ]
        },
        {
          "text": "The company is implementing a durable strategic shift to prioritize long-term user growth and teaching efficacy over short-term monetization, driven by the significant opportunity in AI-powered education.",
          "citations": [
            {
              "source": "Earnings Transcript",
              "chunk_id": "duol_q3_2025_earnings_045"
            },
            {
              "source": "Earnings Transcript",
              "chunk_id": "duol_q3_2025_earnings_067"
            }
          ]
        },
        {
          "text": "This reprioritization is expected to lead to some deceleration in bookings and revenue growth in Q4 and potentially into 2026, as resources are reallocated towards product innovation and user acquisition.",
          "citations": [
            {
              "source": "Earnings Transcript",
              "chunk_id": "duol_q3_2025_earnings_089"
            }
          ]
        },
        {
          "text": "Product developments include expanding content for the top nine languages to a professional proficiency level, introducing guided video calls, and enhancing math and music courses.",
          "citations": [
            {
              "source": "Earnings Transcript",
              "chunk_id": "duol_q3_2025_product_012"
            }
          ]
        },
        {
          "text": "The chess course is the fastest-growing, with player-versus-player (PVP) functionality rolling out.",
          "citations": [
            {
              "source": "Earnings Transcript",
              "chunk_id": "duol_q3_2025_product_034"
            }
          ]
        },
        {
          "text": "Max subscribers now constitute 9% of total subscribers, with bookings doubling year-over-year in Q3, and Max renewals are performing slightly better than Super subscribers.",
          "citations": [
            {
              "source": "Earnings Transcript",
              "chunk_id": "duol_q3_2025_metrics_056"
            }
          ]
        }
      ]
    }
  ],
  "total_items": 1,
  "date_range": {
    "start": "2025-10-01",
    "end": "2025-11-14"
  }
}

Use Cases

Company Intelligence

Monitor multiple companies for material events and updates

Investment Research

Track earnings, guidance, and strategic initiatives

News Aggregation

Build custom financial news feeds for your users

Alert Systems

Create alerts for specific document types or events

Filtering Strategies

By Document Type

# Get only earnings-related content
payload = {
    "tickers": ["AAPL", "MSFT"],
    "doc_types": ["EARNINGS_CALL", "8-K"],
    "limit": 20
}

By Date Range

# Get last 30 days of updates
from datetime import datetime, timedelta

end_date = datetime.now()
start_date = end_date - timedelta(days=30)

payload = {
    "tickers": ["TSLA"],
    "start_date": start_date.strftime("%Y-%m-%d"),
    "end_date": end_date.strftime("%Y-%m-%d")
}

Multiple Tickers

# Monitor a portfolio of companies
payload = {
    "tickers": ["AAPL", "MSFT", "GOOGL", "AMZN", "META"],
    "doc_types": ["EARNINGS_CALL", "NEWS", "PRESS_RELEASE"],
    "limit": 50
}

Pagination

For large result sets, use date-based pagination:

# First request
response1 = requests.post(url, json={
    "tickers": ["AAPL"],
    "limit": 50
})

# Get the oldest date from first batch
oldest_date = response1.json()["items"][-1]["date"]

# Second request - get older items
response2 = requests.post(url, json={
    "tickers": ["AAPL"],
    "end_date": oldest_date,
    "limit": 50
})

Error Responses

{
  "error": {
    "code": "invalid_request",
    "message": "Missing required field: tickers"
  }
}

Best Practices

Limit ticker count per request

For optimal performance, request feeds for 5-10 tickers at a time. For larger portfolios, make multiple parallel requests.

Use date filters wisely

Narrow date ranges improve response times. For real-time monitoring, query the last 7-30 days rather than all historical data.

Cache responses

Feed content doesn’t change frequently. Cache responses for at least 15 minutes to reduce API calls.

Filter by relevant doc types

Specify only the document types you need. This reduces processing time and returns more focused results.

Monitor categories

Use categories to filter and prioritize feed items programmatically based on your use case.

Integration Example

Here’s a complete example of building a company monitoring dashboard:

import requests
from datetime import datetime, timedelta

class FintoolFeedMonitor:
    def __init__(self, api_key):
        self.api_key = api_key
        self.base_url = "https://api.fintool.com/v1/feed"

    def get_portfolio_feed(self, tickers, days=7):
        """Get feed for a portfolio of tickers"""
        end_date = datetime.now()
        start_date = end_date - timedelta(days=days)

        response = requests.post(
            self.base_url,
            headers={
                "Authorization": f"Bearer {self.api_key}",
                "Content-Type": "application/json"
            },
            json={
                "tickers": tickers,
                "doc_types": ["EARNINGS_CALL", "8-K", "NEWS"],
                "start_date": start_date.strftime("%Y-%m-%d"),
                "limit": 100
            }
        )

        return response.json()["items"]

    def filter_by_category(self, items, category):
        """Filter feed items by category"""
        return [
            item for item in items
            if category in item.get("categories", [])
        ]

    def get_earnings_updates(self, tickers):
        """Get only earnings-related updates"""
        items = self.get_portfolio_feed(tickers, days=90)
        return self.filter_by_category(items, "Earnings")

# Usage
monitor = FintoolFeedMonitor("YOUR_API_KEY")

# Monitor tech portfolio
tech_stocks = ["AAPL", "MSFT", "GOOGL", "META", "AMZN"]
recent_updates = monitor.get_portfolio_feed(tech_stocks, days=7)

# Get earnings updates only
earnings = monitor.get_earnings_updates(tech_stocks)

for item in earnings:
    print(f"\n{item['company_name']} - {item['title']}")
    print(f"Date: {item['date']}")
    print(f"Stock: {item['stock_change']['percentage']}%")
    print("\nKey Highlights:")
    for highlight in item['highlights'][:3]:  # Top 3 highlights
        print(f"  • {highlight['text']}")

Getting Started

API Reference

Guides

Overview

Request

Request Example

Response

Response Example

Use Cases

Company Intelligence

Investment Research

News Aggregation

Alert Systems

Filtering Strategies

By Document Type

By Date Range

Multiple Tickers

Categories

Error Responses

Best Practices

Integration Example

Next Steps

Chat Endpoint

Search Endpoint

Getting Started

API Reference

Guides

​Overview

​Request

​Request Example

​Response

​Response Example

​Use Cases

Company Intelligence

Investment Research

News Aggregation

Alert Systems

​Filtering Strategies

​By Document Type

​By Date Range

​Multiple Tickers

​Categories

​Pagination

​Error Responses

​Best Practices

​Integration Example

​Next Steps

Chat Endpoint

Search Endpoint

Overview

Request

Request Example

Response

Response Example

Use Cases

Filtering Strategies

By Document Type

By Date Range

Multiple Tickers

Categories

Pagination

Error Responses

Best Practices

Integration Example

Next Steps