Investor Database API: Filter 10,469 VC, Angel, and PE Firms as JSON in 2026

Every founder I know has burned a week building an investor list: digging through Crunchbase profiles tab by tab, copying partner names into a spreadsheet that is stale before the seed round closes. The data you want is simple, firms plus focus plus contacts, and it is weirdly hard to get in bulk. The shortcut I use now is the Startup Investors Data Scraper on Apify, a queryable investor database of 10,469 firms that returns filtered JSON in one call. Disclosure: the Apify links in this post are affiliate links. If you run the Actor, I may earn a referral commission at no extra cost to you. Is there a public API for investor data? Not really. The big commercial databases keep their APIs behind sales calls and paid plans sized for funds, not founders. Free sources are scattered lists and shared spreadsheets with no filters and no freshness guarantees. This Actor takes a different shape: a curated database of 10,469 investment firms (as of December 2025) that you query like an API, filtering by firm type, sector, stage, and country, and paying only for the records you pull. What the investor database API returns The investor database API returns one JSON record per firm: name, type, description, location, website, social links, assets under management, stages, and sector focus, with partner contacts when you ask for them. Field Example Notes firm_name Acme Ventures With firm_description alongside firm_type_name Venture Capital Investor One of 17 firm types firm_country Germany Plus firm_city and firm_state firm_website https://acme.vc Also firm_linkedin_url, crunchbase_url, twitter_url firm_aum $250M Assets under management when known investor_contacts [{ "job_title": "Partner", ... }] Names, titles, LinkedIn URLs, emails when available, and check sizes, with Include_Contacts on Who this is for Founders building a raise pipeline, sales teams selling into VC and PE back offices, and analysts mapping which firms fund a sector. If your CRM needs 200 seed funds with warm-ish contact info by Friday, this is the fast path. The manual way, and where it breaks The DIY loop is familiar: search "fintech VCs Europe", open thirty tabs, copy names and websites, then hunt each partner on LinkedIn. It produces a list, eventually. The problems compound fast. Coverage is whatever the listicles mention, contacts go stale, there is no consistent schema to filter on, and re-running the exercise next quarter means starting over. Scraping the commercial databases directly gets your account banned and still leaves you without emails. The faster way: run the Startup Investors Data Scraper Apify Console Open the Startup Investors Data Scraper and click Try for free. Pick your filters: Firm_Types, Investment_Stages, Focus_Areas, Countries, and switch on Include_Contacts if you want people, not just firms. Run it and export JSON, CSV, or Excel. REST curl -X POST "https://api.apify.com/v2/acts/johnvc~startup-investors-data-scraper/runs?token=YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "Firm_Types": ["Venture Capital Investor"], "Investment_Stages": ["Seed"], "Countries": ["United States"], "Include_Contacts": true, "Max_Results": 50 }' Enter fullscreen mode Exit fullscreen mode The run and dataset endpoints are documented in the Apify API docs. Query the investor database in Python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("johnvc/startup-investors-data-scraper").call( run_input={ "Investment_Stages": ["Pre-Seed"], "Focus_Areas": ["Artificial Intelligence"], "Include_Contacts": True, "Max_Results": 25, } ) for firm in client.dataset(run["defaultDatasetId"]).iterate_items(): print(firm["firm_name"], firm["firm_country"], firm["firm_website"]) Enter fullscreen mode Exit fullscreen mode Twenty-five pre-seed AI investors, with contacts, in about a minute. Find seed-stage SaaS investors in the US The starter list for most B2B raises. The task Find seed stage SaaS investors in the US shows the stage-plus-sector-plus-country filter combination. Build a list of European fintech VCs with contacts Build a list of European fintech VCs with contacts demonstrates multi-country filtering with Include_Contacts on. Target healthcare angels for a Series A Target healthcare angel investors for a Series A slices the angel firm type against a sector. Find venture debt and corporate VC firms Two often-forgotten pools of capital, each a one-filter query: venture debt firms for non-dilutive funding and corporate venture capital firms with contacts. Let your AI agent build the list via MCP Through Apify's MCP server, Claude, Claude Code, and Cursor can query the database as a tool: ask for "family offices in Singapore that do Series A" and get structured rows back mid-conversation, ready to rank against your thesis. You can read more about Claude at claude.ai. FAQ about scraping investor data Is this investor database scraper free to use? Running it costs money per result pulled, which is the honest trade for maintained data. New Apify accounts include free platform credit, so a first shortlist usually costs nothing out of pocket, and Max_Results caps any run before it starts. Is there a Crunchbase alternative scraper for investor lists? This is the use case where the Actor fits that description. Each record includes a crunchbase_url plus the firm and contact fields you would otherwise assemble by hand, and you query it with filters instead of a subscription. Can my AI agent use this investor scraper over MCP? Yes. Add the Actor through Apify's MCP server and it becomes a callable tool in Claude, Claude Code, or Cursor, which turns "find me investors" from a research project into a prompt. Can I schedule the scraper to keep my pipeline fresh? Yes. Save a filtered query as a task and attach a monthly Apify schedule, and you get a recurring export to diff against your CRM. Set it up from the Startup Investors Data Scraper page. Can the scraper filter by city, like VCs in New York? No, and it is worth being straight about this: the location filter works at the country level via Countries. City and US-state slicing is not an input. You can filter to the United States and then narrow by the returned firm_city and firm_state fields in your own code. More from Truffle Pig Data Same database, other angles: Let Your AI Agent Find Your Investors on Medium, the Startup Investor Database API on LinkedIn, and the Peerlist version. Wrapping up An investor list should be a query, not a quarter-long chore. Run your first filter on the Startup Investors Data Scraper and see who funds your space.