Skip the hour-long listen: structured AI summaries with key takeaways, reported metrics and per-topic sentiment for every S&P 500 call - available within the hour, one GET request away.
# 1. Scan a global watchlist for "agentic AI" mentions in Q1 2026
# → per-ticker mention counts across markets, in one request
curl -sG https://earningscalls.dev/api/v1/search/by_ticker \
-H "X-API-Key: ec_..." \
--data-urlencode 'q="agentic AI"' \
--data-urlencode 'tickers=NVDA,SAP,SHEL' \
--data-urlencode 'date_from=2026-01-01' \
--data-urlencode 'date_to=2026-04-30'
// example response · ~312 ms
{
"query": "\"agentic AI\"",
"tickers_scoped": 3,
"total_companies": 3,
"total_calls": 7,
"results_count": 3,
"results": [
{ "ticker": "NVDA", "company_name": "NVIDIA Corporation", "calls_matched": 4, "last_match_date": "2026-03-17T16:00:00.000Z" },
{ "ticker": "SAP", "company_name": "SAP SE", "calls_matched": 2, "last_match_date": "2026-04-23T21:00:00.000Z" },
{ "ticker": "SHEL", "company_name": "Shell plc", "calls_matched": 1, "last_match_date": "2026-02-05T14:30:00.000Z" }
]
}Four primitives that turn raw earnings calls into a clean dataset your strategy can consume.
Every segment pre-tagged. Five categories with verified counts: executive (826k), analyst (470k), operator (208k), attendee (33k), shareholder (4k). 93% carry the speaker's name.
GET /api/v1/speakers/:idSweep the live archive for phrases like "margin pressure" in one query. Boolean operators, exact phrases, ticker filters across global markets.
GET /api/v1/search?q=…Scan up to 500 tickers in a single request. Per-ticker counts, sector breakdown, last-match date — screen a global universe in one call.
GET /api/v1/search/by_tickerIncremental sync via since / after_id. Re-runnable, idempotent. New calls land within hours of the wire and flow straight into your pipeline.
GET /api/v1/transcripts/recentChange the ticker, click Run, see the actual response.
GET /api/v1/search?q=agentic AI&type=speakers&speaker_type=Executive&ticker=NVDA&limit=5
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Coverage, query semantics, and what the data supports.
A prose summary, main topics each tagged with sentiment, extracted key metrics (revenue, EPS, guidance figures) and a conclusion - all structured JSON from /transcripts/{id}/summary. Schema in the API reference.
S&P 500 calls, generated within the hour of the transcript arriving (transcripts land minutes after the call). The full transcript archive of 248,000+ calls is available regardless via the transcripts API.
Model-generated with a finance-tuned pipeline, consistent structure across calls, and always paired with the source transcript so every claim can be verified against the actual quote. New to earnings calls altogether? Start with what an earnings call is and how to read a transcript like a pro.
Yes - the same summaries are exposed as an MCP tool (get_call_summary) for Claude and other clients. See earnings calls MCP.
What research professionals say about the data and the API.
“Excellent service. Comprehensive coverage of the sectors I wanted and the API is very easy to work with. Highly recommend.”
“Transcripts are accurate, and the API is very user friendly.”
“Connecting Claude through MCP to analyze earnings transcripts has never been easier.”
From the team that brought you the Earnings Calls API - same clean data, same fair pricing.
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