nvNeuralVerge
Startup & Funding Data

Y Combinator Companies Search API and MCP — Filter by Batch, Industry, Region and Team Size

Send a keyword and any of the filters (batches, industries, regions, team size range, hiring, top company, nonprofit) and get matching companies back as JSON: name, link, one-liner, description, batch, status, stage, team size, industries, regions, tags, location, website, hiring flag and launch date. Sort by relevance or newest first.

You send
an optional keyword and filters (batches, industries, regions, team size range, hiring, top company, nonprofit, sort order) plus a max_items cap (up to 250)
You get back
matching companies with one-liner, batch, status, industries, regions, team size and website
Coverage
Y Combinator records with a public page.
Price
1 point per returned record — $1 per 1,000
Billed per record actually returned, capped by max_items. A request that returns nothing costs nothing.
Comparison

Ways to get this data

Three approaches teams use today, and where each one runs into trouble.

ApproachWhat it takesCostTrade-off
Y Combinator directlyType the query into Y Combinator and read the resultsFree, and slowFine for one record, useless across a list, and the layout differs on every platform
Building a scraperWrite it, host it, and repair it when Y Combinator changes its pagesEngineering timeA maintenance commitment for something that isn't your product
NeuralVergeOne request, the same shape as every other source in the catalog$1 per 1,000, misses not billedReturns what Y Combinator publishes at request time. Other platforms are separate sources with the same request format
Response

What you get back

Every field in the example response below.

FieldTypeDescription
session_idstringId of this run, for tracing.
kindstringSource type of the response.
max_itemsnumberThe cap on returned records, as run.
start_pagenumberPage the run started from.
partialbooleanTrue when the run stopped before reaching max_items.
humanstringReadable summary: the query, how many results came back and how many were found.
total_pointsnumberPoints charged for the run.
machine.total_itemsnumberNumber of companies returned in this response.
machine.total_foundnumberTotal matches reported by the platform, when it reports one.
machine.first_item.idstringCompany slug.
machine.first_item.namestringCompany name.
machine.first_item.urlstringLink to the company page.
machine.first_item.aliasstringSlug as the directory uses it.
machine.first_item.yc_idnumberNumeric company id.
machine.first_item.one_linerstringOne-line description.
machine.first_item.descriptionstringLonger description. Shortened in the sample.
machine.first_item.batchstringBatch, e.g. Summer 2013.
machine.first_item.statusstringCompany status, e.g. Public.
machine.first_item.stagestringStage as listed, e.g. Growth.
machine.first_item.team_sizenumberTeam size as listed.
machine.first_item.industrystringTop-level industry.
machine.first_item.subindustrystringIndustry and sub-industry.
machine.first_item.industriesarrayIndustry list.
machine.first_item.regionsarrayRegion list.
machine.first_item.tagsarrayTags.
machine.first_item.locationstringLocation as listed.
machine.first_item.websitestringCompany website.
machine.first_item.logostringLogo URL.
machine.first_item.former_namesarrayEarlier names. Empty in the sample.
machine.first_item.is_hiringbooleanWhether the company is marked as hiring.
machine.first_item.top_companybooleanWhether the company is marked as a top company.
machine.first_item.nonprofitbooleanWhether the company is a nonprofit.
machine.first_item.launched_atstringLaunch date (YYYY-MM-DD).
machine.items[]arrayCompanies returned, same shape as first_item.
machine.page_countnumberPages read for the run.
machine.blockedbooleanWhether the platform refused the request.
machine.proxy_traffic_bytesnumberSize of the data transferred for the run, in bytes.
Response

Example response

A real response, as returned.

{
  "session_id": "11111111-1111-1111-1111-111111111111",
  "kind": "yc_companies_search",
  "max_items": 2,
  "start_page": 1,
  "partial": false,
  "human": "# Y Combinator — companies search\n\n- **Query:** max_items=2\n- **Results:** 2 of 6283 found\n- **Proxy traffic:** 7.0 KB",
  "machine": {
    "total_items": 2,
    "first_item": {
      "id": "doordash",
      "name": "DoorDash",
      "url": "https://www.ycombinator.com/companies/doordash",
      "alias": "doordash",
      "yc_id": 531,
      "one_liner": "Restaurant delivery.",
      "description": "Founded in 2013, DoorDash is a San Francisco-based technology company passionate about transforming local businesses and dedicated to enabling new ways of working, earning, and living. Today, DoorDash",
      "batch": "Summer 2013",
      "status": "Public",
      "stage": "Growth",
      "team_size": 8600,
      "industry": "Consumer",
      "subindustry": "Consumer -> Food and Beverage",
      "industries": [
        "Consumer",
        "Food and Beverage"
      ],
      "regions": [
        "United States of America",
        "America / Canada"
      ],
      "tags": [
        "Marketplace",
        "E-commerce"
      ],
      "location": "San Francisco, CA, USA",
      "website": "http://doordash.com",
      "logo": "https://bookface-images.s3.amazonaws.com/small_logos/d13287c52acc96909f32342e85c26a33cfdac310.png",
      "former_names": [],
      "is_hiring": true,
      "top_company": true,
      "nonprofit": false,
      "launched_at": "2013-05-02"
    },
    "items": [
      {
        "id": "doordash",
        "name": "DoorDash",
        "url": "https://www.ycombinator.com/companies/doordash",
        "alias": "doordash",
        "yc_id": 531,
        "one_liner": "Restaurant delivery.",
        "description": "Founded in 2013, DoorDash is a San Francisco-based technology company passionate about transforming local businesses and dedicated to enabling new ways of working, earning, and living. Today, DoorDash",
        "batch": "Summer 2013",
        "status": "Public",
        "stage": "Growth",
        "team_size": 8600,
        "industry": "Consumer",
        "subindustry": "Consumer -> Food and Beverage",
        "industries": [
          "Consumer",
          "Food and Beverage"
        ],
        "regions": [
          "United States of America",
          "America / Canada"
        ],
        "tags": [
          "Marketplace",
          "E-commerce"
        ],
        "location": "San Francisco, CA, USA",
        "website": "http://doordash.com",
        "logo": "https://bookface-images.s3.amazonaws.com/small_logos/d13287c52acc96909f32342e85c26a33cfdac310.png",
        "former_names": [],
        "is_hiring": true,
        "top_company": true,
        "nonprofit": false,
        "launched_at": "2013-05-02"
      },
      {
        "id": "airbnb",
        "name": "Airbnb",
        "url": "https://www.ycombinator.com/companies/airbnb",
        "alias": "airbnb",
        "yc_id": 271,
        "one_liner": "Book accommodations around the world.",
        "description": "Founded in August of 2008 and based in San Francisco, California, Airbnb is a trusted community marketplace for people to list, discover, and book unique accommodations around the world — online or fr",
        "batch": "Winter 2009",
        "status": "Public",
        "stage": "Growth",
        "team_size": 6132,
        "industry": "Consumer",
        "subindustry": "Consumer -> Travel, Leisure and Tourism",
        "industries": [
          "Consumer",
          "Travel, Leisure and Tourism"
        ],
        "regions": [
          "United States of America",
          "America / Canada"
        ],
        "tags": [
          "Marketplace",
          "Travel"
        ],
        "location": "San Francisco, CA, USA",
        "website": "http://airbnb.com",
        "logo": "https://bookface-images.s3.amazonaws.com/small_logos/3e9a0092bee2ccf926e650e59c06503ec6b9ee65.png",
        "former_names": [],
        "is_hiring": false,
        "top_company": true,
        "nonprofit": false,
        "launched_at": "2012-01-17"
      }
    ],
    "total_found": 6283,
    "page_count": 1,
    "blocked": false,
    "proxy_traffic_bytes": 7212
  },
  "total_points": 2
}
Integration

How to run it

The same lookup works from the app, the API, or as a tool an agent can call mid-task.

Results come back in the same envelope as every other source: a session id, a readable summary, the structured result and the points charged. max_items caps how many records are returned and billed.

curl -X POST https://api.neuralverge.ai/functions/v1/run-yc-companies-search \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"max_items":2}'
Use cases

What teams use it for

Where this field shows up in an actual workflow.

Batch lists

Pull every company in a batch or set of batches for research or outreach lists.

Sector and region scans

Filter by industry and region, such as Fintech in Europe, and read size and status.

Hiring and growth screens

Filter to companies marked as hiring, within a team size range.

Coverage & limits

Coverage, freshness and limits

What this source covers, how fresh it is, and where it stops.

Coverage

Y Combinator records with a public page.

Freshness

Read at request time, so the answer reflects the platform as it stands when you ask.

Handling

This source returns information Y Combinator shows publicly. Every response carries the session id you can trace.

What it will not do
  • —Filters are applied by the directory; the source does not add its own scoring or de-duplication.
  • —The directory does not give funding amounts or valuations.
  • —Results are capped by max_items (up to 250); use start_page to continue past the first page.
FAQ

Questions, answered

Send them comma-separated, for example "Winter 2024, Summer 2024".

Related

Related sources

Try y combinator companies search on your own data

One request format across every source in the catalog.

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