Linkedin Employees Scraper
Pricing
$39.00/month + usage
Go to Store
Linkedin Employees Scraper
Effortlessly gather LinkedIn URLs and names of employees in bulk. Ideal for HR and recruitment, this tool quickly provides essential contact information, simplifying talent search and networking opportunities.
2.6 (13)
Pricing
$39.00/month + usage
41
Total users
1.2k
Monthly users
166
Runs succeeded
>99%
Response time
11 days
Last modified
4 days ago
You can access the Linkedin Employees Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1{
2 "openapi": "3.0.1",
3 "info": {
4 "version": "0.0",
5 "x-build-id": "oOTsFTfOrflRg52yF"
6 },
7 "servers": [
8 {
9 "url": "https://api.apify.com/v2"
10 }
11 ],
12 "paths": {
13 "/acts/caprolok~linkedin-employees-scraper/run-sync-get-dataset-items": {
14 "post": {
15 "operationId": "run-sync-get-dataset-items-caprolok-linkedin-employees-scraper",
16 "x-openai-isConsequential": false,
17 "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
18 "tags": [
19 "Run Actor"
20 ],
21 "requestBody": {
22 "required": true,
23 "content": {
24 "application/json": {
25 "schema": {
26 "$ref": "#/components/schemas/inputSchema"
27 }
28 }
29 }
30 },
31 "parameters": [
32 {
33 "name": "token",
34 "in": "query",
35 "required": true,
36 "schema": {
37 "type": "string"
38 },
39 "description": "Enter your Apify token here"
40 }
41 ],
42 "responses": {
43 "200": {
44 "description": "OK"
45 }
46 }
47 }
48 },
49 "/acts/caprolok~linkedin-employees-scraper/runs": {
50 "post": {
51 "operationId": "runs-sync-caprolok-linkedin-employees-scraper",
52 "x-openai-isConsequential": false,
53 "summary": "Executes an Actor and returns information about the initiated run in response.",
54 "tags": [
55 "Run Actor"
56 ],
57 "requestBody": {
58 "required": true,
59 "content": {
60 "application/json": {
61 "schema": {
62 "$ref": "#/components/schemas/inputSchema"
63 }
64 }
65 }
66 },
67 "parameters": [
68 {
69 "name": "token",
70 "in": "query",
71 "required": true,
72 "schema": {
73 "type": "string"
74 },
75 "description": "Enter your Apify token here"
76 }
77 ],
78 "responses": {
79 "200": {
80 "description": "OK",
81 "content": {
82 "application/json": {
83 "schema": {
84 "$ref": "#/components/schemas/runsResponseSchema"
85 }
86 }
87 }
88 }
89 }
90 }
91 },
92 "/acts/caprolok~linkedin-employees-scraper/run-sync": {
93 "post": {
94 "operationId": "run-sync-caprolok-linkedin-employees-scraper",
95 "x-openai-isConsequential": false,
96 "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
97 "tags": [
98 "Run Actor"
99 ],
100 "requestBody": {
101 "required": true,
102 "content": {
103 "application/json": {
104 "schema": {
105 "$ref": "#/components/schemas/inputSchema"
106 }
107 }
108 }
109 },
110 "parameters": [
111 {
112 "name": "token",
113 "in": "query",
114 "required": true,
115 "schema": {
116 "type": "string"
117 },
118 "description": "Enter your Apify token here"
119 }
120 ],
121 "responses": {
122 "200": {
123 "description": "OK"
124 }
125 }
126 }
127 }
128 },
129 "components": {
130 "schemas": {
131 "inputSchema": {
132 "type": "object",
133 "required": [
134 "companyUrls",
135 "maxResultsPerCompany"
136 ],
137 "properties": {
138 "companyUrls": {
139 "title": "Company URLs",
140 "type": "array",
141 "description": "Enter the company URLs whose employees you want to extract",
142 "items": {
143 "type": "string"
144 }
145 },
146 "designation": {
147 "title": "Search Job Title",
148 "type": "array",
149 "description": "Enter the specific job titles (Ex: CEO, CFO, HR Manager, etc.)",
150 "items": {
151 "type": "string"
152 }
153 },
154 "maxResultsPerCompany": {
155 "title": "Max Results Per Company",
156 "type": "integer",
157 "description": "Limit the no. of results you want to extract per company",
158 "default": 20
159 }
160 }
161 },
162 "runsResponseSchema": {
163 "type": "object",
164 "properties": {
165 "data": {
166 "type": "object",
167 "properties": {
168 "id": {
169 "type": "string"
170 },
171 "actId": {
172 "type": "string"
173 },
174 "userId": {
175 "type": "string"
176 },
177 "startedAt": {
178 "type": "string",
179 "format": "date-time",
180 "example": "2025-01-08T00:00:00.000Z"
181 },
182 "finishedAt": {
183 "type": "string",
184 "format": "date-time",
185 "example": "2025-01-08T00:00:00.000Z"
186 },
187 "status": {
188 "type": "string",
189 "example": "READY"
190 },
191 "meta": {
192 "type": "object",
193 "properties": {
194 "origin": {
195 "type": "string",
196 "example": "API"
197 },
198 "userAgent": {
199 "type": "string"
200 }
201 }
202 },
203 "stats": {
204 "type": "object",
205 "properties": {
206 "inputBodyLen": {
207 "type": "integer",
208 "example": 2000
209 },
210 "rebootCount": {
211 "type": "integer",
212 "example": 0
213 },
214 "restartCount": {
215 "type": "integer",
216 "example": 0
217 },
218 "resurrectCount": {
219 "type": "integer",
220 "example": 0
221 },
222 "computeUnits": {
223 "type": "integer",
224 "example": 0
225 }
226 }
227 },
228 "options": {
229 "type": "object",
230 "properties": {
231 "build": {
232 "type": "string",
233 "example": "latest"
234 },
235 "timeoutSecs": {
236 "type": "integer",
237 "example": 300
238 },
239 "memoryMbytes": {
240 "type": "integer",
241 "example": 1024
242 },
243 "diskMbytes": {
244 "type": "integer",
245 "example": 2048
246 }
247 }
248 },
249 "buildId": {
250 "type": "string"
251 },
252 "defaultKeyValueStoreId": {
253 "type": "string"
254 },
255 "defaultDatasetId": {
256 "type": "string"
257 },
258 "defaultRequestQueueId": {
259 "type": "string"
260 },
261 "buildNumber": {
262 "type": "string",
263 "example": "1.0.0"
264 },
265 "containerUrl": {
266 "type": "string"
267 },
268 "usage": {
269 "type": "object",
270 "properties": {
271 "ACTOR_COMPUTE_UNITS": {
272 "type": "integer",
273 "example": 0
274 },
275 "DATASET_READS": {
276 "type": "integer",
277 "example": 0
278 },
279 "DATASET_WRITES": {
280 "type": "integer",
281 "example": 0
282 },
283 "KEY_VALUE_STORE_READS": {
284 "type": "integer",
285 "example": 0
286 },
287 "KEY_VALUE_STORE_WRITES": {
288 "type": "integer",
289 "example": 1
290 },
291 "KEY_VALUE_STORE_LISTS": {
292 "type": "integer",
293 "example": 0
294 },
295 "REQUEST_QUEUE_READS": {
296 "type": "integer",
297 "example": 0
298 },
299 "REQUEST_QUEUE_WRITES": {
300 "type": "integer",
301 "example": 0
302 },
303 "DATA_TRANSFER_INTERNAL_GBYTES": {
304 "type": "integer",
305 "example": 0
306 },
307 "DATA_TRANSFER_EXTERNAL_GBYTES": {
308 "type": "integer",
309 "example": 0
310 },
311 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
312 "type": "integer",
313 "example": 0
314 },
315 "PROXY_SERPS": {
316 "type": "integer",
317 "example": 0
318 }
319 }
320 },
321 "usageTotalUsd": {
322 "type": "number",
323 "example": 0.00005
324 },
325 "usageUsd": {
326 "type": "object",
327 "properties": {
328 "ACTOR_COMPUTE_UNITS": {
329 "type": "integer",
330 "example": 0
331 },
332 "DATASET_READS": {
333 "type": "integer",
334 "example": 0
335 },
336 "DATASET_WRITES": {
337 "type": "integer",
338 "example": 0
339 },
340 "KEY_VALUE_STORE_READS": {
341 "type": "integer",
342 "example": 0
343 },
344 "KEY_VALUE_STORE_WRITES": {
345 "type": "number",
346 "example": 0.00005
347 },
348 "KEY_VALUE_STORE_LISTS": {
349 "type": "integer",
350 "example": 0
351 },
352 "REQUEST_QUEUE_READS": {
353 "type": "integer",
354 "example": 0
355 },
356 "REQUEST_QUEUE_WRITES": {
357 "type": "integer",
358 "example": 0
359 },
360 "DATA_TRANSFER_INTERNAL_GBYTES": {
361 "type": "integer",
362 "example": 0
363 },
364 "DATA_TRANSFER_EXTERNAL_GBYTES": {
365 "type": "integer",
366 "example": 0
367 },
368 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
369 "type": "integer",
370 "example": 0
371 },
372 "PROXY_SERPS": {
373 "type": "integer",
374 "example": 0
375 }
376 }
377 }
378 }
379 }
380 }
381 }
382 }
383 }
384}Linkedin Employees Scraper OpenAPI definition
OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for Linkedin Employees Scraper from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients:
