# Seeking Alpha Scraper — Valuation, Dividends, Ratings (`bovi/seeking-alpha-scraper`) Actor

Scrape Seeking Alpha for a dense per-ticker valuation snapshot — price, market cap, P/E, P/S, P/B, EPS, dividends, margins, 52-week range, Wall-St rating, analyst targets, and SA Quant ranks. Plus dividend history and company profiles. No API key. Pay per result.

- **URL**: https://apify.com/bovi/seeking-alpha-scraper.md
- **Developed by:** [Vitalii Bondarev](https://apify.com/bovi) (community)
- **Categories:** Business, Developer tools, MCP servers
- **Features:** Limited permissions
- **Stats:** 13 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $18.43 / 1,000 ticker snapshots

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

### Seeking Alpha Scraper — Dividends, Ratings & Company Profiles

Extract stock analysis data from Seeking Alpha — dividend history, company overviews, analyst ratings, and company profiles. No API key required. Pay per result.

### Use cases

- **Dividend research:** Build a dividend income tracker by pulling 2 years of payment history for your watchlist (amount, ex-date, pay-date, frequency).
- **Stock screener data:** Enrich a portfolio spreadsheet with live P/E ratio, market cap, 52-week range, and analyst consensus ratings.
- **Financial monitoring:** Automate alerts when sector, employees, or description data changes for target companies.
- **Quant / AI pipelines:** Feed structured stock metadata into LLM analysis, ML models, or data warehouses without paying $25–599/mo for official data APIs.

### Input

| Field | Type | Description |
|-------|------|-------------|
| `tickers` | string\[] | Stock ticker symbols, e.g. `AAPL`, `MSFT`, `TSLA`, `NVDA` |
| `dataTypes` | string\[] | What to fetch: `overview`, `dividends`, `profile` (default: `overview`) |
| `maxItems` | integer | Max total records. 0 = no limit (default: 100) |
| `proxyConfiguration` | object | Apify Proxy settings. RESIDENTIAL recommended |

### Output

#### Overview record

```json
{
  "ticker": "AAPL",
  "data_type": "overview",
  "name": "Apple Inc.",
  "price": 192.35,
  "currency": "USD",
  "market_cap": 4428825400000,
  "shares_outstanding": 14687356000,
  "pe_ratio": 36.55,
  "pe_ratio_fwd": 34.47,
  "ps_ratio": 9.88,
  "pb_ratio": 41.53,
  "ev_ebitda": 27.30,
  "eps_ttm": 8.25,
  "dividend_yield_ttm": 0.35,
  "dividend_yield_fwd": 0.36,
  "payout_ratio": 12.58,
  "dividend_growth_5y": 4.69,
  "roe": 141.47,
  "gross_margin": 47.86,
  "net_margin": 27.15,
  "revenue_growth_yoy": 12.76,
  "week52_high": 317.4,
  "week52_low": 195.07,
  "return_1y_pct": 47.87,
  "wall_st_rating": 4.02,
  "analyst_price_target": 310.51,
  "analysts_buy": 23,
  "analysts_hold": 15,
  "analysts_sell": 1,
  "quant_overall_rank": 695,
  "quant_sector_rank": 108,
  "sa_authors_count": 14,
  "sector": "Information Technology",
  "industry": "Technology Hardware, Storage and Peripherals",
  "parse_confidence": "HIGH",
  "scraped_at": "2026-06-09T10:00:00Z"
}
```

`wall_st_rating` is the Wall-Street analyst consensus (1 = strong sell … 5 = strong buy).
`quant_*_rank` are Seeking Alpha's Quant ranks (lower = stronger). `sa_authors_*` (not shown in
full above) is the SA contributor rating distribution: strong_buy / buy / hold / sell / strong_sell counts.

#### Dividend record

```json
{
  "ticker": "AAPL",
  "data_type": "dividends",
  "amount": 0.25,
  "currency": "USD",
  "ex_dividend_date": "2026-02-07",
  "payment_date": "2026-02-13",
  "frequency": "quarterly",
  "parse_confidence": "HIGH",
  "scraped_at": "2026-06-09T10:00:00Z"
}
```

### Notes

- Uses Seeking Alpha's internal v3 API (headless, no browser required)
- Access resilient: rotates to a fresh RESIDENTIAL IP per ticker on any block (up to 6 tries) — reliable on large batches
- Polite ~1s pacing between requests per ticker

### 💰 Pricing & how we compare

**Pay-per-result (PPE): $19 / 1K snapshots ($0.019 each).** You are billed per `ticker-snapshot` actually returned — plus the tiny
`apify-actor-start` fee Apify waives for short runs. No subscription, no API key, no proxy fee on top.

**Our edge:** ONE dense snapshot per ticker (50+ fields) — price, market cap, PE (GAAP/non-GAAP/fwd), P/S, P/B, EV/EBITDA, EPS, dividend yields + payout + 5y growth, ROE, gross/net margin, revenue growth, 52-week range, 1y/YTD return, **Wall-St analyst rating (1–5) + price target + buy/hold/sell**, **SA Quant ranks**, **SA Authors rating distribution**, sector/industry — not one row per article. No rival returns this consolidated valuation snapshot.

**Pricing examples** (pay only for what you get, minus Apify's 20%):

| Volume | Cost |
|---|---|
| 100 snapshots | $1.90 |
| 1,000 snapshots | $19.00 |
| 10,000 snapshots | $190.00 |

#### How rivals price the same job (live Apify Store, checked 2026-06-09)

| Actor | Their price | What they lack vs us |
|---|---|---|
| `parseforge/seekingalpha-scraper` | $0.021 / result | per-article rows, not a consolidated ticker snapshot |
| `fortuitous_pirate/seekingalpha-stock-analysis-scraper` | $0.02 + $0.15 start | 1★, per-article |
| `doesaiknow/seeking-alpha-api-news-dividend-data` | $0.005 / item | cheaper but news/dividend feed, not a valuation snapshot |

*Prices above are competitors' live Store prices at the time of writing; ours is set to sit just
below the strongest comparable while returning richer, quality-scored data.*

### 🤖 Use with AI agents (MCP)

This actor is agent-ready (category **MCP_SERVERS**). Point any MCP client (Claude Desktop, Cursor,
n8n AI, LangGraph) at it:

```json
{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?actors=bovi/seeking-alpha-scraper",
      "headers": { "Authorization": "Bearer <YOUR_APIFY_TOKEN>" }
    }
  }
}
```

### More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

- [Companies France](https://apify.com/bovi/companies-france)
- [Companies House UK Scraper](https://apify.com/bovi/companies-house-uk)
- [Crunchbase Scraper](https://apify.com/bovi/crunchbase-scraper)
- [Transfermarkt Scraper](https://apify.com/bovi/transfermarkt-scraper)
- [Unusual Options Activity](https://apify.com/bovi/unusual-options-activity)
- [Yahoo Finance Scraper](https://apify.com/bovi/yahoo-finance-scraper)

Chain any of them together from the **Integrations** tab (the *Run succeeded* trigger) to build a multi-step workflow — one actor's output feeds the next.

### Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as `USAGE_STATS` in your own Apify key-value store, so you can see the exact record created for your run.

Set `disableUsageStats` to `true` in the input to opt out. Nothing is sent then; your `USAGE_STATS` record only says that statistics were disabled.

Only these fields are recorded:

- schema version, Actor name and build number;
- UTC start and finish hour (not a precise timestamp);
- run duration, number of results and time to the first result, each as a coarse range;
- whether the result was empty, the end status, and an error type from a fixed list;
- memory setting and counts of charged events;
- names of the input fields you set, never their values;
- the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

#### Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same `disableUsageStats: true` input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

#### Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

- the result limit you asked for (a range, when the input has one) and what share of it was delivered;
- results delivered per input item you listed (a range);
- output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
- how the run was started (console, API, schedule, webhook, another Actor);
- how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
- if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
- a short code made from the names of the input fields you set, never their values.

#### Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and `disableUsageStats: true` turns it off.

# Actor input Schema

## `tickers` (type: `array`):

Stock ticker symbols to scrape, e.g. AAPL, MSFT, TSLA, NVDA. Up to 100 per run.

## `dataTypes` (type: `array`):

What data to fetch for each ticker. overview: price, market cap, P/E, dividend yield, 52-week range. dividends: dividend payment history. profile: company description, sector, employees, founded.

## `maxItems` (type: `integer`):

Maximum total records to return across all tickers and data types. 0 = no limit.

## `proxyConfiguration` (type: `object`):

Apify Proxy settings. RESIDENTIAL recommended for reliability.

## `disableUsageStats` (type: `boolean`):

See the README Usage statistics section for details.

## Actor input object example

```json
{
  "tickers": [
    "AAPL",
    "MSFT"
  ],
  "dataTypes": [
    "overview"
  ],
  "maxItems": 100,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  },
  "disableUsageStats": false
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset containing Seeking Alpha Scraper records (ticker, name, price, market_cap, pe_ratio, dividend_yield_ttm, wall_st_rating, analyst_price_target, quant_overall_rank, sector, scraped_at, parse_confidence).

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "tickers": [
        "AAPL",
        "MSFT"
    ],
    "dataTypes": [
        "overview"
    ],
    "maxItems": 100,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("bovi/seeking-alpha-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "tickers": [
        "AAPL",
        "MSFT",
    ],
    "dataTypes": ["overview"],
    "maxItems": 100,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("bovi/seeking-alpha-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "tickers": [
    "AAPL",
    "MSFT"
  ],
  "dataTypes": [
    "overview"
  ],
  "maxItems": 100,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call bovi/seeking-alpha-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,bovi/seeking-alpha-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/JXh3TFVeWkSn9LUrw/builds/QhSK5IuKkVzWgs7dy/openapi.json