# US Medical & Health Professional License Scraper (`scrapers_lat/usa-medical-licenses-scraper`) Actor
Scrape US state medical and health professional licenses: licensee name, license number, profession, specialty, status, practice address (city, state, ZIP) and issue and expiration dates. Filter by keyword, profession, city or status. Export to JSON, CSV or Excel.
- **URL**: https://apify.com/scrapers\_lat/usa-medical-licenses-scraper.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $15.30 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## US Medical & Health Professional License Scraper
> Pull a clean, structured register of US medical and health professional licenses: physicians, physician assistants, radiologic technologists, respiratory care practitioners and more. Every record has the licensee name, license number, profession, specialty, status, practice address and issue and expiration dates. Filter by keyword, profession, city or status and export ready-to-use leads.
**๐ฅ [Input](https://apify.com/scrapers_lat/usa-medical-licenses-scraper/input-schema) ยท ๐ค [Output](https://apify.com/scrapers_lat/usa-medical-licenses-scraper/output-schema) ยท ๐ฐ [Pricing](https://apify.com/scrapers_lat/usa-medical-licenses-scraper/pricing) ยท โถ๏ธ [Examples](https://apify.com/scrapers_lat/usa-medical-licenses-scraper/examples)**
Verified licensees name + license number
Practice address city / state / ZIP
JSON / CSV / Excel output formats
### Who is it for
| Use case | Who benefits |
|---|---|
| Lead generation | Medical device, staffing and SaaS vendors building physician outreach lists |
| Recruiting | Healthcare recruiters sourcing licensed clinicians by profession and city |
| Credential checks | Teams verifying license number, status and expiration |
| Research | Analysts studying the supply and distribution of health professionals |
### How to use it
1. Add one or more **search keywords** (for example a specialty or a city), or leave it empty to list everything that matches your filters.
2. Optionally narrow by **professions**, **cities** and **license status**.
3. Set **Max Licenses To Scrape** and run. Export as JSON, CSV or Excel, or pull it through the Apify API.
### Frequently Asked Questions
**Which professions are covered?**
Physicians and a wide range of health professionals, including physician assistants, medical radiologic technologists, respiratory care practitioners, medical physicists and more. Use the professions filter to focus on one.
**Can I get only currently licensed professionals?**
Yes. Set status to active to keep only currently licensed professionals, inactive for the rest, or all for both.
**Do records include a practice address?**
Most active licensees include a practice street address, city, state and ZIP. When the source has no address on file those fields are null.
**How fresh is the data?**
Records are read live at run time, so each reflects the register at the moment of the run (see observedAt).
### Related scrapers
- [NPPES NPI Healthcare Provider Data Scraper](https://apify.com/scrapers_lat/nppes-npi-scraper)
- [New York Professional License Scraper (OP)](https://apify.com/scrapers_lat/ny-professions-scraper)
- [Texas TDLR License & Contractor Records Scraper](https://apify.com/scrapers_lat/texas-tdlr-scraper)
### More scrapers at scrapers.lat
This actor is built and maintained by [scrapers.lat](https://scrapers.lat), where we publish scrapers for public platforms: finance, news, real estate, jobs, e-commerce and government data. Browse the full catalog or ask us for a custom scraper at [scrapers.lat](https://scrapers.lat).
---
> This actor is an independent tool and accesses only publicly available license records. It has no affiliation with any licensing authority. Use the results in accordance with the source's terms and applicable law.
# Actor input Schema
## `searchQueries` (type: `array`):
Optional. One or more keywords matched across the whole record (name, profession, specialty, city). One run does many searches. For example 'CARDIOLOGY', 'PEDIATRICS', 'HOUSTON'. Leave empty to list all licenses that match the filters below.
## `professions` (type: `array`):
Optional. Keep only these professions / license types (partial match). For example 'Physician', 'Physician Assistant', 'Respiratory Care', 'Radiologic Technologist'.
## `cities` (type: `array`):
Optional. Keep only licensees whose practice address is in these cities. For example 'HOUSTON', 'DALLAS', 'AUSTIN'.
## `status` (type: `string`):
Which licenses to return: active (currently licensed), inactive, or all.
## `maxLicenses` (type: `integer`):
Maximum number of licensees to collect. Optional.
## Actor input object example
```json
{
"searchQueries": [
"CARDIOLOGY"
],
"status": "active",
"maxLicenses": 50
}
````
# Actor output Schema
## `results` (type: `string`):
No description
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"searchQueries": [
"CARDIOLOGY"
],
"maxLicenses": 50
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/usa-medical-licenses-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"searchQueries": ["CARDIOLOGY"],
"maxLicenses": 50,
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/usa-medical-licenses-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"searchQueries": [
"CARDIOLOGY"
],
"maxLicenses": 50
}' |
apify call scrapers_lat/usa-medical-licenses-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/usa-medical-licenses-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "US Medical & Health Professional License Scraper",
"description": "Scrape US state medical and health professional licenses: licensee name, license number, profession, specialty, status, practice address (city, state, ZIP) and issue and expiration dates. Filter by keyword, profession, city or status. Export to JSON, CSV or Excel.",
"version": "0.1",
"x-build-id": "vdV8zIHPqdytF1ukz"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~usa-medical-licenses-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-usa-medical-licenses-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~usa-medical-licenses-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-usa-medical-licenses-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~usa-medical-licenses-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-usa-medical-licenses-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"searchQueries": {
"title": "Search Keywords",
"type": "array",
"description": "Optional. One or more keywords matched across the whole record (name, profession, specialty, city). One run does many searches. For example 'CARDIOLOGY', 'PEDIATRICS', 'HOUSTON'. Leave empty to list all licenses that match the filters below.",
"items": {
"type": "string"
}
},
"professions": {
"title": "Professions / License Types",
"type": "array",
"description": "Optional. Keep only these professions / license types (partial match). For example 'Physician', 'Physician Assistant', 'Respiratory Care', 'Radiologic Technologist'.",
"items": {
"type": "string"
}
},
"cities": {
"title": "Practice Cities",
"type": "array",
"description": "Optional. Keep only licensees whose practice address is in these cities. For example 'HOUSTON', 'DALLAS', 'AUSTIN'.",
"items": {
"type": "string"
}
},
"status": {
"title": "License Status",
"enum": [
"active",
"inactive",
"all"
],
"type": "string",
"description": "Which licenses to return: active (currently licensed), inactive, or all.",
"default": "active"
},
"maxLicenses": {
"title": "Max Licenses To Scrape",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Maximum number of licensees to collect. Optional."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```