Startup & Funding Data
Wellfound Company API and MCP — Stage, Funding, Founders, Open Jobs
Send a Wellfound company slug, or the link to its page, and get the company as JSON: tagline and description, company size, stage, total raised, markets, tags, locations, funding rounds, founders, open jobs and the number of live jobs by role.
- You send
- a Wellfound company slug, or the link to its company page
- You get back
- description, size, stage, total raised, funding rounds, founders, tags, locations and open jobs
- Coverage
- Wellfound records with a public page.
- Price
- 5 pts — $5 per 1,000
- Charged only when the record resolves. A request that finds nothing is not billed.
Comparison
Ways to get this data
Three approaches teams use today, and where each one runs into trouble.
| Approach | What it takes | Cost | Trade-off |
|---|---|---|---|
| Wellfound directly | Open the page on Wellfound and read it | Free, and slow | Fine for one record, useless across a list, and the layout differs on every platform |
| Building a scraper | Write it, host it, and repair it when Wellfound changes its pages | Engineering time | A maintenance commitment for something that isn't your product |
| NeuralVerge | One request, the same shape as every other source in the catalog | $5 per 1,000, misses not billed | Returns what Wellfound 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.
| Field | Type | Description |
|---|---|---|
session_id | string | Id of this run, for tracing. |
kind | string | Source type of the response, here wellfound_companies. |
company | string | The slug or URL you sent. |
company_id | string | The company slug as the platform uses it. |
human | string | Readable summary of the record. |
machine.blocked | boolean | Whether the platform refused the request. |
total_points | number | Points charged for the run. |
machine.company.id | string | Numeric company id, as a string. |
machine.company.alias | string | Company slug. |
machine.company.name | string | Company name. |
machine.company.url | string | Link to the company page. |
machine.company.tagline | string | One-line tagline. |
machine.company.description | string | Company description. |
machine.company.logo_url | string | Logo image link. |
machine.company.website_url | string | Company website. |
machine.company.linkedin_url | string | Company LinkedIn link. |
machine.company.twitter_url | string | Company X link. |
machine.company.facebook_url | string | Company Facebook link. |
machine.company.blog_url | string | Company blog link. |
machine.company.producthunt_url | string | Linked Product Hunt page. |
machine.company.company_size | string | Size band, for example 5000+. |
machine.company.stage | string | Company stage as labelled on Wellfound. |
machine.company.total_raised_amount | number | Total raised. |
machine.company.hiring | boolean | Whether the company is hiring. |
machine.company.is_operating | null | Operating flag; null in the sample. |
machine.company.live_jobs_count | number | Number of live jobs. |
machine.company.tags | array | Tag labels. |
machine.company.markets | array | Market labels. |
machine.company.locations | array | Locations. |
machine.company.company_types | array | Company type labels. |
machine.company.funding_rounds | array | Rounds with id, round_type, closed_at and valuation. |
machine.company.founders | array | Founders with name, role, title, profile_url, avatar_url and bio. |
machine.company.jobs | array | Open jobs with id, title, url, type, locations, remote, compensation, equity, experience range, posted_at and snippet. |
machine.company.job_counts_by_role | array | Open jobs per role as role and count. |
machine.company.culture_images | array | Image links from the company page. |
machine.pages_opened | number | Number of pages read for the run. |
Response
Example response
A real response, as returned.
{
"session_id": "11111111-1111-1111-1111-111111111111",
"kind": "wellfound_companies",
"company": "stripe",
"company_id": "stripe",
"human": "# Wellfound — company\n\n- **Id:** stripe\n- **Pages opened:** 1\n- **Proxy traffic:** 174.4 KB\n- **Name:** Stripe\n- **Tagline:** A new, comprehensive and clean standard for online payment processing\n- **Size:** 5000+\n- **Stage:** Scale Stage\n- **Website:** https://stripe.com",
"machine": {
"company": {
"id": "37232",
"alias": "stripe",
"name": "Stripe",
"url": "https://wellfound.com/company/stripe",
"tagline": "A new, comprehensive and clean standard for online payment processing",
"description": "Stripe is a software platform for starting and running internet businesses. Millions of businesses rely on Stripe’s software tools to accept payments, expand globally, and manage their businesses onli",
"logo_url": "https://photos.wellfound.com/startups/i/37232-b86e6247bcd9846c18c91fe65ca0355d-medium_jpg.jpg?buster=1610581275",
"website_url": "https://stripe.com",
"linkedin_url": "http://www.linkedin.com/company/stripe",
"twitter_url": "http://twitter.com/stripe",
"facebook_url": "https://www.facebook.com/stripehq",
"blog_url": "https://stripe.com/blog",
"producthunt_url": "https://www.producthunt.com/posts/stripe-elements-2",
"company_size": "5000+",
"stage": "Scale Stage",
"total_raised_amount": 8138000000,
"hiring": true,
"is_operating": null,
"live_jobs_count": 138,
"tags": [
"B2B",
"Top Investors"
],
"markets": [
"Internet",
"SaaS"
],
"locations": [
"Chicago",
"New York City"
],
"company_types": [
"Startup",
"Web Development"
],
"funding_rounds": [
{
"id": "199807",
"round_type": "Series I",
"closed_at": "2023-03-16",
"valuation": null
},
{
"id": "180221",
"round_type": "Series G",
"closed_at": "2020-04-16",
"valuation": null
}
],
"founders": [
{
"name": "John Collison",
"role": "Founder",
"title": null,
"profile_url": "https://wellfound.com/p/collision",
"avatar_url": "https://photos.wellfound.com/users/47880-medium_jpg?1405470059",
"bio": "Co-founder at @ Stripe"
},
{
"name": "Patrick Collison",
"role": "Founder",
"title": null,
"profile_url": "https://wellfound.com/p/patrick-collison",
"avatar_url": "https://photos.wellfound.com/users/10228-medium_jpg?1405442666",
"bio": "Cofounder of @ Stripe . Previously: MIT, Auctomatic, reverse engineering iPhone apps, reading books."
}
],
"jobs": [
{
"id": "4823135",
"title": "Machine Learning Engineer, Radar",
"slug": "machine-learning-engineer-radar",
"url": "https://wellfound.com/jobs/4823135-machine-learning-engineer-radar",
"job_type": "full_time",
"locations": [
"Seattle"
],
"remote": false,
"remote_kind": "ONSITE",
"compensation": "",
"equity": null,
"years_experience_min": 2,
"years_experience_max": null,
"posted_at": "2026-10-07",
"snippet": "Build, train, evaluate, and deploy ML models that detect fraud across Stripe’s global payments network Research emerging fraud patterns like token theft and develop ML solutions to address them"
},
{
"id": "4822053",
"title": "Software Engineer, Internal Identity",
"slug": "software-engineer-internal-identity",
"url": "https://wellfound.com/jobs/4822053-software-engineer-internal-identity",
"job_type": "full_time",
"locations": [
"Seattle"
],
"remote": false,
"remote_kind": "ONSITE",
"compensation": "",
"equity": null,
"years_experience_min": 2,
"years_experience_max": 5,
"posted_at": "2026-10-07",
"snippet": "Build and maintain reliable, performant and scalable authorization infrastructure (e.g. libraries, frameworks, services). Build comprehensive understanding of authorization needs of our users (e.g. pr"
}
],
"job_counts_by_role": [
{
"role": "Designer",
"count": 7
},
{
"role": "Engineering",
"count": 69
}
],
"culture_images": [
"https://d2gn4xht817m0g.cloudfront.net/p/media_uploads/images/original/000/527/818/527818-a8379971b624c0128e0ee835ab5d45d25bbf9b40.jpg?1568694959",
"https://d2gn4xht817m0g.cloudfront.net/p/media_uploads/images/original/000/527/819/527819-3897684d9fb2a80c80670da020b7146c141f3e3c.jpg?1568694969"
]
},
"blocked": false,
"pages_opened": 1,
"proxy_traffic_bytes": 178558
},
"total_points": 5
}Integration
How to run it
The same lookup works from the app, the API, or as a tool an agent can call mid-task.
One record per request. Results come back in the same envelope as every other source: a session id, a readable summary, the structured result and the points charged.
curl -X POST https://api.neuralverge.ai/functions/v1/run-wellfound-companies \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"company":"stripe"}'Use cases
What teams use it for
Where this field shows up in an actual workflow.
Account research
Get size, stage, funding and locations for a startup before outreach.
Hiring signals
Use live_jobs_count and job_counts_by_role to see which functions a company is growing.
Funding history
Read round types and dates for a company next to its stage.
Company enrichment
Add Wellfound links, tags and markets to companies in your own database.
Coverage & limits
Coverage, freshness and limits
What this source covers, how fresh it is, and where it stops.
Coverage
Wellfound 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 Wellfound shows publicly. Every response carries the session id you can trace.
What it will not do
- —Round amounts and valuations are often null; the sample shows round type and close date only.
- —The page lists founders with their public profile text. Use it for company research, not to profile individuals.
- —Compensation and equity on jobs are often empty.
FAQ
Questions, answered
Yes, a list of open jobs with title, location, remote type and a snippet, plus counts by role. For a search across companies use Wellfound job search.
Related
Related sources
Try wellfound company on your own data
One request format across every source in the catalog.