Screener.in Company Financials Scraper

Export Screener.in company financials for recurring Indian equity research. Search by company name or supply company URLs to collect public consolidated identity, market metrics, quarterly results, annual profit and loss, balance sheets, cash flow, ratios and shareholding history in one structured bundle per company.

This is for analysts maintaining valuation workbooks, researchers refreshing issuer fundamentals, and portfolio teams comparing public reporting periods. It does not require a Screener account or export premium content.

What does this Actor extract?

Data	Output
Company identity	Source ID, name, URL identifier, NSE symbol and BSE code when linked
Market metrics	Visible top-ratio labels and source text including units
Quarterly results	Public consolidated table with original periods
Annual results	Profit and loss, including TTM when exposed
Balance sheet	Visible consolidated asset and liability rows
Cash flow	Visible operating, investing and financing rows
Ratios	Public table with days, percentages and established units
Shareholding	Public category percentages and shareholder counts

Each financial cell preserves its source text as well as a parsed number. Amounts stay in INR crore; the Actor does not convert currencies or scales. EPS uses INR/share, percentages stay as percentage points (72.41 means 72.41%), and shareholder counts remain counts. Unknown ratio units are null.

Who is it for?

Use these records for issuer-comparison workbooks, fundamental research and portfolio reporting refreshes. This tool is not a trading signal service.

Why use this Actor?

A company bundle keeps identity and reporting basis beside the financial history, avoiding ambiguous piles of standalone cells. Period labels and source URLs support spreadsheet joins and audit trails. Blank source cells remain null rather than becoming misleading zeros.

Only consolidated pages are accepted. The Actor does not silently substitute standalone results or claim that every listed issuer publishes every section.

Getting started

1. Keep the prefilled TCS company URL for a first run, or enter company searches.
2. Set Maximum companies to the number of company bundles needed.
3. Run the Actor and inspect the default dataset's Company financials view.
4. Download JSON for nested tables, or transform the rows into your workbook.
5. Use an Apify schedule if you want recurring snapshots. Store and compare snapshots downstream; this Actor does not send change alerts itself.

Input parameters

Field	Meaning
startUrls	Up to 25 objects containing public Screener company URLs
queries	Up to ten company-name or symbol searches, each 1–100 characters
maxItems	Global distinct-company limit; default 3, minimum 1, maximum 25

At least one URL or search query is required. Queries are trimmed and sent to Screener autocomplete; source-ranked suggestions are not exact-match filters. A query may return fewer suggestions than the requested limit. This is not an exhaustive exchange-wide financial screening or custom screener-query service.

Explicit URLs take precedence. Duplicates are normalized to the same consolidated URL. Search discovery fills remaining places in input order and stops at the global limit. Source suggestions pointing only to standalone accounts are skipped. An explicit standalone-only issuer fails clearly. No login, cookie, proxy or premium-data input is supported.

{
  "queries": ["tata"],
  "maxItems": 2
}

For a known issuer, use:

{
  "startUrls": [{"url": "https://www.screener.in/company/TCS/consolidated/"}],
  "maxItems": 3
}

Output example

This shortened excerpt shows the real structure observed for TCS. Full output includes all visible cells from each supported table, not just this excerpt. Values are snapshots and will change with the source.

{
  "sourceUrl": "https://www.screener.in/company/TCS/consolidated/",
  "companyId": "3365",
  "companyName": "Tata Consultancy Services Ltd",
  "symbol": "TCS",
  "reportingBasis": "consolidated",
  "nseSymbol": "TCS",
  "bseCode": "532540",
  "tables": [{
    "section": "profit-loss",
    "sourceUnit": "INR crore (except percentages and per-share rows)",
    "rows": [{
      "label": "Sales",
      "values": [{"period": "Mar 2026", "periodEnd": "2026-03-31", "raw": "267,021", "value": 267021, "unit": "INR crore"}]
    }]
  }]
}

Other top-level fields are website, metrics, unavailableSections and scrapedAt. Source dates are preserved when available; periodEnd is null where no date key exists, including TTM. scrapedAt is extraction time, not an exchange quote timestamp. Website links are returned, never crawled.

How much does it cost to extract Screener.in company financials?

Pay-per-event billing uses a $0.005 start fee and one item event per company bundle. All included tables and cells have no separate event charge. Rejected URLs, duplicate companies and empty search results produce no item charge. The start fee still applies to a valid search with no matches.

Plan	Per company
FREE	$0.0046
BRONZE	$0.004
SILVER	$0.00312
GOLD	$0.0024
PLATINUM	$0.0024
DIAMOND	$0.0024

Worked examples at BRONZE, including the start fee:

• 1 company × $0.004 + $0.005 = $0.009 total.
• 5 companies × $0.004 + $0.005 = $0.025 total.
• 25 companies × $0.004 + $0.005 = $0.105 total.

Spend tiers depend on qualifying aggregate monthly Store spend, not a private per-Actor volume schedule. Check the current Apify pricing tab before use. These are modeled Actor event totals, not payout guarantees; refunds, fraud, disputes, taxes, corrections and clawbacks can affect payouts.

Limits and failure behavior

• Public visible consolidated tables only; no premium exports or forecasts.
• No peer-comparison rows, segment drilldowns, filings or historical revisions.
• No standalone reporting mode or automatic financial advice.
• Source history length varies by issuer and section; no fixed year-count promise.
• Requests are sequential, direct HTTP; transient network errors, 429 and 5xx receive at most three attempts with bounded delays. No paid proxy fallback.
• A permanent block, missing company identity, standalone response or missing core statements fails the run. It is not reported as a successful empty export.
• A legitimate search with no consolidated suggestions succeeds with zero rows.
• Previously saved rows can remain after a later error; treat them as partial.
• Billing limits may stop collection before maxItems. It is an upper bound.

Integrations

Keep JSON in S3 or a warehouse for scheduled issuer snapshots. In Make, Zapier or n8n, trigger a downstream workflow after a successful Actor run, fetch the default dataset, and flatten tables[].rows[].values[] into rows keyed by company ID, section, label and period. Join those records in Google Sheets, Excel or a research database. JSON preserves nested data better than CSV.

API usage

Set APIFY_TOKEN in your environment; do not paste it into shared URLs. The synchronous endpoint below is suitable for small requests. For larger collections start asynchronously, retain the run ID, and fetch its dataset after successful completion rather than starting duplicate runs.

curl -X POST -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  'https://api.apify.com/v2/acts/automation-lab~screener-in-company-financials/run-sync-get-dataset-items' \
  -d '{"queries":["tata"],"maxItems":2}'

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/screener-in-company-financials').call({ queries: ['tata'], maxItems: 2 });
const { items } = await client.dataset(run.defaultDatasetId).listItems({ limit: 2 });
console.log(items);

import os
from apify_client import ApifyClient
client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('automation-lab/screener-in-company-financials').call(run_input={'queries': ['tata'], 'maxItems': 2})
items = client.dataset(run['defaultDatasetId']).list_items(limit=2).items
print(items)

MCP use

For Claude Code, select this Actor explicitly:

claude mcp add --transport http apify \
  'https://mcp.apify.com?tools=automation-lab/screener-in-company-financials'

Claude Desktop, Cursor, and VS Code: use the equivalent configuration below when your client/version supports remote HTTP MCP:

{"mcpServers":{"apify":{"url":"https://mcp.apify.com?tools=automation-lab/screener-in-company-financials"}}}

Authenticate through your client's supported Apify flow. Discover actual tool names and argument schemas with scoped tools/list. Actor selection also exposes run, dataset, key-value and abort helpers, not exactly one tool.

Example prompt: “Collect two Tata company consolidated financials, then show annual sales periods with units and source URLs. Do not offer investment advice.”

Start an authorized run once, retain its run/storage IDs, and follow the SAME run. call-actor waits at most 45 seconds (default 30); IDs are metadata, not financial rows. If still running, use get-actor-run with 2/4/8-second backoff capped at ten seconds and a total 120-second deadline. Set client timeout above the selected server wait plus transport margin. On timeout recover the known run instead of restarting; if its ID is unknown, report uncertainty. At the deadline report pending with the run ID and stop. Failures and partial rows must be described honestly.

After success, use get-dataset-items with explicit fields, offset and limit. For example, process pages of 20 source rows, at most 100 rows and 64 KiB of serialized result content admitted to model context, whichever comes first. Enforce bytes host-side even for one oversized company bundle; omit or summarize with disclosure. If your client cannot intercept oversized responses, do not claim a hard byte guarantee. Track source offsets, report truncation and the next offset, and keep full exports outside model context. These are consumer context limits, not changes to the Actor's supported collection contract. No universal tool-token or caching savings are promised.

Legality

Use the applicable Apify standard terms. The Actor performs no AI inference and sends no input or financial data to an AI model. The generated illustration is independent branding, not a source logo.

Data handling and support

Collected output is public issuer identity and financial data; no personal shareholder identities are requested. Apify stores datasets, input and logs under your account's retention settings until expiry or deletion. Delete run storages through Apify when no longer needed. No external cache or session store is maintained. For help, open an issue on this Actor's Apify page with the run ID and a non-sensitive reproduction.

Responsible use and diagnostics

Use public data responsibly, respect source terms and applicable rights, and verify financial figures against issuer filings before making decisions. This independent tool is not affiliated with Screener.in, NSE, BSE or any issuer. It does not bypass account access, provide licensed premium content or guarantee investment accuracy.

Failed operations send sanitized diagnostic input, exceptions and actor/build/run IDs to our private GlitchTip service for repair. Secret fields and URL queries are removed and reports are retained for 30 days. Do not submit credentials.

FAQ and troubleshooting

Why did search return an unexpected company? Screener autocomplete supplies ranked suggestions rather than an exact ticker filter. Use an explicit company URL when issuer identity must be exact.

Why is a section missing? Public coverage varies. Check unavailableSections; missing annual profit/loss or balance-sheet data instead fails the run.

Why are some values null? Empty or nonnumeric source cells are not zeros. Unknown units and absent period date keys also remain null.

Can I obtain standalone accounts or peers? No. Only the consolidated visible financial tables described above are supported.

What if requests are blocked? Reduce frequency and retry later after checking the source page. The Actor never charges an item for a blocked company, though already delivered companies and the valid run start can have charges.

Related Actors

For other public market datasets, see our TradingView Stock Screener Scraper and Google Finance Stock Quotes Scraper. These are complementary sources, not substitutes for Screener statements.