Hunter·Company search

Count reachable people

/discover/peoplesync$0 / call

Same filters as /discover, but adds the total personal and generic email counts across every matching company (meta.total_emails). Free. Use it to size a campaign before paying for domain searches.

Input

querystring
Describe the companies in plain language instead of using filters, e.g. "Series A fintech companies in Europe". Hunter's assistant turns it into filters.
organizationobject
Limit to specific companies: { "domain": ["stripe.com"] } or { "name": ["Stripe"] }.
headquarters_locationobject
HQ filter: { "include": [{ "country": "US" }, { "continent": "Europe" }], "exclude": [{ "country": "BE" }] }. Keys: continent, country (ISO-2), state (US code), city.
industryobject
Industry filter: { "include": ["Financial Services"], "exclude": ["Staffing and Recruiting"] }. Uses LinkedIn industry names.
headcountarray
Employee ranges to include, any of: "1-10", "11-50", "51-200", "201-500", "501-1000", "1001-5000", "5001-10000", "10001+".
company_typeobject
Company type filter: { "include": ["privately held"], "exclude": ["non profit", "government agency", "educational"] }.
year_foundedobject
Founding year: { "from": 2015, "to": 2022 } or { "include": [2020, 2021] }.
keywordsobject
Keyword filter over company descriptions: { "match": "any" | "all", "include": ["payments"], "exclude": ["crypto"] }.
technologyobject
Technologies detected on the company's site: { "match": "any" | "all", "include": ["salesforce", "hubspot"] }.
fundingobject
Funding filter, e.g. { "stage": { "include": ["series_a"] } } or amount ranges. See Hunter's Discover docs for keys.
similar_toarray
Domains of companies to find look-alikes of, e.g. ["stripe.com"].

Field	Type	Required	Description
query	string	—	Describe the companies in plain language instead of using filters, e.g. "Series A fintech companies in Europe". Hunter's assistant turns it into filters.
organization	object	—	Limit to specific companies: { "domain": ["stripe.com"] } or { "name": ["Stripe"] }.
headquarters_location	object	—	HQ filter: { "include": [{ "country": "US" }, { "continent": "Europe" }], "exclude": [{ "country": "BE" }] }. Keys: continent, country (ISO-2), state (US code), city.
industry	object	—	Industry filter: { "include": ["Financial Services"], "exclude": ["Staffing and Recruiting"] }. Uses LinkedIn industry names.
headcount	array	—	Employee ranges to include, any of: "1-10", "11-50", "51-200", "201-500", "501-1000", "1001-5000", "5001-10000", "10001+".
company_type	object	—	Company type filter: { "include": ["privately held"], "exclude": ["non profit", "government agency", "educational"] }.
year_founded	object	—	Founding year: { "from": 2015, "to": 2022 } or { "include": [2020, 2021] }.
keywords	object	—	Keyword filter over company descriptions: { "match": "any" \| "all", "include": ["payments"], "exclude": ["crypto"] }.
technology	object	—	Technologies detected on the company's site: { "match": "any" \| "all", "include": ["salesforce", "hubspot"] }.
funding	object	—	Funding filter, e.g. { "stage": { "include": ["series_a"] } } or amount ranges. See Hunter's Discover docs for keys.
similar_to	array	—	Domains of companies to find look-alikes of, e.g. ["stripe.com"].

Run it

curl -s https://sooma.dev/v1/run \ -H "Authorization: Bearer $SOOMA_API_KEY" \ -H "Content-Type: application/json" \ -d '{"provider":"hunterio","endpoint":"/discover/people","input":{"industry":{"include":["Financial Services"]},"headquarters_location":{"include":[{"country":"US"}]}}}'

Or ask your agent: it will call inspect for this schema and run it over MCP.