Earnings Call Transcript API - SEC 8-K Filings Parser & Monitor

Get earnings call transcripts with per-speaker tagging and separated Q&A, plus SEC 8-K filings parsed item by item from EDGAR, as clean structured JSON. One API covers both the words executives said on the call and the material events they filed with the SEC.

Pay-per-result with no start fee and no subscription. A low-cost structured alternative to expensive market data subscriptions that return transcripts as one raw text blob and filings as bare links.

What you get

Earnings call transcripts (structured, not a text blob):

• Every speaker turn tagged with name, role, and role type (executive, analyst, operator)
• Prepared remarks separated from the Q&A session
• Q&A pairs: each analyst question matched with the management answers that follow, with analyst firm affiliations
• Call participants roster, fiscal quarter, call date, word and question counts
• Guidance sentences extracted from executive speech
• Finance-dictionary sentiment scores (positive, negative, uncertainty, net)

SEC 8-K filings (parsed, not just linked):

• Full item-code classification across the complete 8-K item map, 1.01 through 9.01: earnings (2.02), executive changes (5.02), cybersecurity incidents (1.05), bankruptcies (1.03), M&A (1.01, 2.01), and every other item
• Per-item parsed text from the primary document
• Press release exhibits (EX-99.1) parsed into headline, outlook section, and body
• Guidance sentence extraction with quantity and period matching, so generic optimism is filtered out
• EDGAR acceptance timestamps for latency-sensitive event studies
• Direct EDGAR links to the filing index, primary document, and press release

Full-text keyword search: search any word or phrase across 8-K filings from ALL US companies (for example "guidance withdrawal", "material weakness", "going concern") with date and item filters.

Monitoring mode: turn on onlyNew with a schedule and each run emits only newly filed 8-Ks and newly published transcripts. A metadataOnly cheap mode powers lightweight alerting.

What you do NOT get

• No audio and no real-time streaming of live calls. Transcripts typically appear within hours of the call.
• Transcript coverage spans roughly 1,000 to 1,500 mostly large and mid cap US companies per earnings quarter, with an archive back to about 2007. Every US filer's 8-Ks are covered, but not every micro cap has a transcript.
• Sentiment scores come from a deterministic finance-domain dictionary, not an LLM. Reproducible and fast, but not a language-model judgment.
• No 10-K or 10-Q financial statements and no XBRL fundamentals. This actor is about 8-K events and earnings calls.

Use cases

• LLM training and RAG pipelines: export clean question-answer pairs and speaker-tagged remarks, ready for fine-tuning and retrieval corpora.
• Event-driven trading research: track 8-K item codes with acceptance timestamps, e.g. earnings releases (Item 2.02) or executive departures (Item 5.02), the moment EDGAR disseminates them.
• Guidance monitoring: extract forward-looking sentences from press releases and calls for a watchlist, and diff them quarter over quarter.
• Cross-market screening: full-text search every US filer's 8-Ks for crisis language such as "going concern" or "restatement".
• Compliance and IR competitive tracking: follow what peer companies file and say, in a machine-readable format.

When to use this actor

	This actor	Typical market data APIs
Earnings transcripts	Speaker-tagged turns, Q&A pairs, roles	Often one raw text blob, or gated to a top tier (FMP transcripts are Ultimate-only at $149/mo billed annually)
8-K filings	Parsed items, press release text, guidance, sentiment	Usually metadata and links only
Filing search	Full-text across all US filers	Often a separate product (sec-api.io starts at $49/mo)
Pricing	Pay-per-result, no start fee, no subscription	$49 to $149+ per month, annual commitments
Structure for AI agents	JSON records, MCP-ready	Varies

If you need every ticker's transcript back to the 1990s or real-time call audio, a premium vendor is the right tool. For structured transcripts and parsed filings on demand, this actor does it for a fraction of a cent per record.

🔌 Integrations: Automate SEC 8-K and Earnings Monitoring

A single run answers one question ("what did NVDA say last quarter?"). The real value comes from running this API repeatedly, so new 8-K filings and fresh transcripts land in your stack the moment they publish. See the full list of Apify platform integrations.

Tasks and Schedules (the core recipe). Save one task per thing you watch (a ticker watchlist, or a searchKeyword screener like "material weakness"), turn on onlyNew, then attach a schedule from the actor's Actions, then Schedule menu. Each run then emits only records you have not seen. Useful cron strings: 0 6 * * * (daily 6 AM), 0 */6 * * * (every 6 hours), 0 13 * * 1-5 (weekday mornings, UTC), 0 9 * * 1 (Mondays). One schedule can trigger many tasks at once.

n8n. This API ships an n8n community node (see the n8n integration section below). A four-step monitor: Schedule Trigger, then the Earnings Call Transcript API node with onlyNew on, then a Filter on itemCodes containing 2.02, then Slack or email.

Make and Zapier. The same pattern works no-code with Make and Zapier: trigger on a schedule, run the actor, route the new records where you need them.

Store the history (Supabase). Send each run's rows into a table so a filing and transcript history accumulates. No-code: the n8n Actor node, then a Supabase node. Or in Python (each row carries recordType, ticker, itemCodes, sentimentNet, guidanceSentences):

from apify_client import ApifyClient
from supabase import create_client

apify = ApifyClient("YOUR_APIFY_TOKEN")
supabase = create_client("YOUR_SUPABASE_URL", "YOUR_SUPABASE_KEY")

run = apify.actor("johnvc/earnings-call-transcript-api").call(run_input={
    "tickers": ["NVDA", "AAPL", "MSFT"],
    "dataType": "both",
    "onlyNew": True,
})
rows = list(apify.dataset(run["defaultDatasetId"]).iterate_items())
supabase.table("earnings_events").upsert(rows).execute()

MCP and AI agents. Add this API as a tool in Claude or Cursor through the Apify MCP server so an agent can pull live filings and transcripts (see the Use this API from Claude section below).

Webhooks. For anything custom, fire an Apify webhook on ACTOR.RUN.SUCCEEDED to push each run's dataset into your own service.

Pricing

One event, charged per record returned: a parsed 8-K filing or a structured transcript. Error rows are never charged. There is no start fee and no separate subscription.

Worked example: 100 records cost about one cent. A quarterly refresh of a 50-ticker watchlist (one earnings 8-K plus one transcript each) is 100 records.

Input

Field	Type	Required	Default	Notes
tickers	array	one of tickers / searchKeyword	["AAPL"]	Stock symbols or CIK numbers
dataType	enum	yes	both	filings, transcripts, or both
filingsLimit	integer	no	10	Max 8-K filings per ticker (1-200); caps total results in keyword mode
transcriptsLimit	integer	no	4	Max transcripts per ticker (1-40), newest first
searchKeyword	string	one of tickers / searchKeyword	-	Full-text search across ALL US filers; treats dataType as filings
eventCategories	array	no	-	Shortcuts like earnings, executive_changes, cybersecurity that map to item codes
itemCodes	array	no	-	Exact 8-K item codes, e.g. ["2.02"]
dateFrom / dateTo	string	no	last ~12 months	YYYY-MM-DD window
includeFullText	boolean	no	false	Adds complete filing, press release, and transcript text
metadataOnly	boolean	no	false	Skip document parsing; metadata and item codes only
onlyNew	boolean	no	false	Emit only records not returned by previous runs (monitoring)

Example input

Ticker mode, filings and transcripts together:

{
    "tickers": ["AAPL", "NVDA", "MSFT"],
    "dataType": "both",
    "filingsLimit": 5,
    "transcriptsLimit": 1
}

Keyword mode, screening every US filer:

{
    "searchKeyword": "guidance withdrawal",
    "dataType": "filings",
    "filingsLimit": 25
}

Sample output

Filing record (trimmed):

{
    "recordType": "filing",
    "ticker": "AAPL",
    "companyName": "Apple Inc.",
    "cik": "0000320193",
    "formType": "8-K",
    "accessionNumber": "0000320193-26-000011",
    "filedDate": "2026-04-30",
    "acceptanceDateTime": "2026-04-30T20:30:41.000Z",
    "eventDate": "2026-04-30",
    "itemCodes": ["2.02", "9.01"],
    "itemNames": ["Results of Operations and Financial Condition", "Financial Statements and Exhibits"],
    "title": "Apple Inc. 8-K: Results of Operations and Financial Condition (Item 2.02)",
    "items": [{"itemCode": "2.02", "itemName": "Results of Operations and Financial Condition", "text": "On April 30, 2026, Apple Inc. issued a press release regarding..."}],
    "pressRelease": {"headline": "Apple reports second quarter results", "outlookText": null, "text": "..."},
    "guidanceSentences": [],
    "sentiment": {"positive": 18.94, "negative": 16.57, "uncertainty": 6.31, "wordCount": 1267, "netScore": 0.067},
    "sentimentNet": 0.067,
    "url": "https://www.sec.gov/Archives/edgar/data/320193/000032019326000011/",
    "documentUrl": "https://www.sec.gov/Archives/edgar/data/320193/000032019326000011/aapl-20260430.htm",
    "pressReleaseUrl": "https://www.sec.gov/Archives/edgar/data/320193/000032019326000011/a8-kex991q2202603282026.htm"
}

Transcript record (trimmed):

{
    "recordType": "transcript",
    "ticker": "AAPL",
    "companyName": "Apple Inc.",
    "title": "Apple AAPL Q2 2026 Earnings Call Transcript",
    "eventDate": "2026-04-30",
    "fiscalQuarter": "Q2 2026",
    "fiscalYear": 2026,
    "participants": [{"name": "Timothy D. Cook", "role": "Chief Executive Officer", "roleType": "executive"}],
    "preparedRemarks": [{"speaker": "Timothy D. Cook", "role": "Chief Executive Officer", "roleType": "executive", "text": "..."}],
    "qaPairs": [{
        "question": {"speaker": "Erik Woodring", "affiliation": "Morgan Stanley", "text": "..."},
        "answers": [{"speaker": "Timothy D. Cook", "role": "Chief Executive Officer", "text": "..."}]
    }],
    "guidanceSentences": ["We expect June quarter revenue to grow..."],
    "sentiment": {"positive": 21.4, "negative": 6.2, "uncertainty": 8.9, "wordCount": 11842, "netScore": 0.637},
    "sentimentNet": 0.637,
    "speakerCount": 13,
    "questionCount": 16
}

How to get started

1. Open the actor on Apify: View on Apify Store
2. Enter one or more tickers (or a search keyword) and click Start.
3. Read your records from the run's dataset as JSON, CSV, or Excel.

For a Python quick-start and MCP setup walkthrough, see the example repo on GitHub.

8-K data comes from SEC EDGAR (https://www.sec.gov/cgi-bin/browse-edgar), the SEC's official filing system. No API key is required.

Run from the API

curl -X POST "https://api.apify.com/v2/acts/johnvc~earnings-call-transcript-api/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"tickers": ["NVDA"], "dataType": "both", "filingsLimit": 5, "transcriptsLimit": 1}'

🔌 Use this API from Claude (MCP)

Add this actor as a tool in Claude Code (free trial), Claude Cowork (free trial), or any other MCP client, via the hosted Apify MCP server. Use this actor-specific URL:

https://mcp.apify.com/?tools=actors,docs,johnvc/earnings-call-transcript-api

Setup walkthrough:

Apify MCP integration docs: https://docs.apify.com/platform/integrations/mcp

Your AI agent can then answer questions like "What guidance did NVDA give on its last earnings call?" or "Which companies filed 8-Ks mentioning material weakness this month?" with live structured data.

n8n integration

Available as an n8n community node, n8n-nodes-earnings-call-transcript-api. In n8n: Settings, Community Nodes, install n8n-nodes-earnings-call-transcript-api, then use it in any workflow. It ships Filing and Transcript resources, a full-text Search operation, and works as an AI Agent tool.

Applications: Earnings Call Transcript & 8-K Examples

Ready-to-run examples of this API in action. Open any one and run it in a single click.

SEC EDGAR 8-K Filings API by Ticker

Pull parsed 8-K filings for any ticker from SEC EDGAR as structured JSON. Run this task

8-K Filing API: Item Codes, Guidance, Sentiment

Get 8-K filings with classified item codes, guidance sentences, and sentiment. Run this task

NVDA Earnings Call Transcript API in JSON

Speaker-tagged NVIDIA earnings call transcript with Q&A pairs and sentiment. Run this task

AAPL Earnings Call Transcript API in JSON

Apple's latest earnings call as structured JSON, prepared remarks separated from Q&A. Run this task

MSFT Earnings Call Transcript API in JSON

Microsoft earnings call transcript with per-speaker roles and guidance sentences. Run this task

TSLA Earnings Call Transcript API in JSON

Tesla earnings call transcript, Q&A pairs matched to analyst firms. Run this task

AMZN Earnings Call Transcript API in JSON

Amazon earnings call transcript as clean structured records. Run this task

META Earnings Call Transcript API in JSON

Meta earnings call transcript with sentiment scores and participant roster. Run this task

GOOGL Earnings Call Transcript API in JSON

Alphabet earnings call transcript, prepared remarks and Q&A separated. Run this task

AMD Earnings Call Transcript API in JSON

AMD earnings call transcript with speaker tagging and finance-dictionary sentiment. Run this task

NFLX Earnings Call Transcript API in JSON

Netflix earnings call transcript as JSON, ready for RAG and analysis. Run this task

AVGO Earnings Call Transcript API in JSON

Broadcom earnings call transcript with Q&A pairs and guidance extraction. Run this task

SEC 8-K Item 5.02 Executive Departure Tracker

Track executive departures and appointments the moment they hit EDGAR. Run this task

SEC 8-K Cybersecurity Incident Monitor (1.05)

Monitor Item 1.05 material cybersecurity incident disclosures across all filers. Run this task

SEC 8-K Item 2.02 Earnings Release Feed

A feed of Item 2.02 earnings releases with parsed press release text. Run this task

SEC 8-K Material Events Watchlist Monitor

Watch a ticker list for any material 8-K event on a schedule. Run this task

Material Weakness Disclosure Screener (SEC)

Full-text screen every US filer's 8-Ks for "material weakness" language. Run this task

Going Concern Warning Screener (SEC 8-K)

Surface going-concern language across recent 8-K filings. Run this task

Guidance Withdrawal Screener (SEC Filings)

Find companies withdrawing or cutting guidance in their filings. Run this task

Financial Restatement Screener (SEC 8-K)

Screen 8-K filings for financial restatement disclosures. Run this task

Earnings Call Q&A Pairs Dataset for LLM & RAG

Export matched analyst-question and management-answer pairs as a training corpus. Run this task

Earnings Guidance Monitor (Calls & 8-K)

Track forward-looking guidance sentences from calls and press releases quarter over quarter. Run this task

🔗 Related Tools

Building a market-intelligence pipeline? These tools from the same catalog pair well with 8-K filings and earnings transcripts:

• Google Finance API: live quotes, financials, and market data to pair with the events you track here.
• Congress Financial Disclosures & Stock Trades: another primary-source financial signal, congressional trades filed with the government.
• Crunchbase Company API: company firmographics, funding rounds, and investors for the names on your watchlist.
• Investment Finance Professionals (SEC adviser contacts): contact data for SEC-registered investment advisers.

Alternatives such as nexgendata/earnings-transcripts exist, but charge on the order of $0.50 per record (several thousand times the per-record cost here) and show minimal adoption. This API returns speaker-tagged transcripts and item-parsed 8-Ks as clean JSON, pay-per-result, with no start fee.

FAQ

Which companies have transcripts?

Roughly 1,000 to 1,500 mostly large and mid cap US companies per earnings quarter, with an archive reaching back to about 2007. 8-K filings cover every US public filer without exception. If a transcript is not available for a ticker, the run returns a clear uncharged note instead of failing.

How fresh is the data?

8-K records are available minutes after EDGAR accepts the filing; the record carries the exact acceptance timestamp. Transcripts typically publish within hours of the call for large caps, and up to a day or two for smaller names.

What do the 8-K item codes mean?

Every 8-K reports numbered items. The most watched: 2.02 results of operations (earnings), 5.02 executive departures and appointments, 1.05 material cybersecurity incidents, 1.03 bankruptcy, 2.01 completed acquisitions, 7.01 Regulation FD disclosures, 8.01 other events. The actor classifies all items from 1.01 through 9.01 and includes human-readable names in every record.

Is the sentiment score from an LLM?

No. Scores come from a deterministic finance-domain dictionary (positive, negative, and uncertainty word counts per 1,000 words, with negation handling). The same document always produces the same score, which matters for research reproducibility.

Why did I get fewer results than my limit?

The limits are maximums. A company may have fewer 8-Ks in the date window, or fewer transcripts than requested. In keyword mode, only filings matching your phrase count toward the limit.

Can I search filings without a ticker?

Yes. Set searchKeyword and leave tickers empty to run a full-text search across all US filers. Add tickers to narrow the search to specific companies.

Can I monitor filings on a schedule?

Yes. Enable onlyNew and add a schedule in Apify. Each run then emits only records that previous runs have not returned, which is ideal for alerting pipelines. Combine with metadataOnly for the cheapest possible polling. See the Integrations section above for the full Tasks-and-Schedules recipe with cron examples.

What is an 8-K filing?

An 8-K is the "current report" US public companies file with the SEC to announce material events between quarterly reports: earnings, executive changes, acquisitions, bankruptcies, cybersecurity incidents, and more. This API parses each 8-K from SEC EDGAR into item codes, press release text, and guidance sentences. Background: Form 8-K.

What does an earnings call transcript include?

Each transcript record separates prepared remarks from the Q&A session, tags every speaker with name, role, and role type (executive, analyst, operator), matches each analyst question to the management answers that follow, and adds guidance sentences and finance-dictionary sentiment. See earnings call for background.

Should I use an API or a web scraper for earnings data?

Both, and this actor is both. An official market-data API is usually rate limited, quota bound, and gates transcripts behind a high tier, while a plain web scraper returns messy HTML. This actor gives you the clean, structured result of a purpose-built API: call it yourself, pay per record, no quotas, and get the same JSON whether you want one ticker or a full-text screen of every filer.

Can I use this API programmatically?

Yes. The Apify API runs the actor, schedules it, and fetches datasets, and the apify-client package exists for both Node.js and Python. See the Run from the API section above, or the actor's API tab.

Can I use the Earnings Call Transcript API through an MCP server?

Yes. Add it as a tool in any MCP client (Claude, Cursor, and others) through the hosted Apify MCP server with the actor-specific URL https://mcp.apify.com/?tools=actors,docs,johnvc/earnings-call-transcript-api. In Claude Code (free trial) or Claude Cowork (free trial) your agent can then answer questions like "what guidance did NVDA give last quarter?" with live data. See the Apify MCP docs.

Can I integrate this API with other apps?

Yes. It connects to almost any cloud service through Apify integrations: Make, Zapier, Slack, the n8n community node, and webhooks on ACTOR.RUN.SUCCEEDED for custom actions. See the Integrations section above for full recipes.

How else can I collect SEC and market data?

Pair this API with related tools in the same catalog: the Google Finance API for quotes and financials, Congress Financial Disclosures & Stock Trades for another primary-source signal, and the Crunchbase Company API for company funding and firmographics.

Last Updated: 2026.07.27