
Linkedin Post Scraper
Pricing
$14.99/month + usage

Linkedin Post Scraper
Extract rich, structured data from LinkedIn posts with our high-performance, AI-friendly scraping solution. Perfect for content analysis, social listening, and market research.
0.0 (0)
Pricing
$14.99/month + usage
0
Total users
12
Monthly users
12
Runs succeeded
79%
Response time
2.5 days
Last modified
a month ago
You can access the Linkedin Post Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1{
2 "openapi": "3.0.1",
3 "info": {
4 "version": "0.0",
5 "x-build-id": "mZJZ5lVvln36oT4CP"
6 },
7 "servers": [
8 {
9 "url": "https://api.apify.com/v2"
10 }
11 ],
12 "paths": {
13 "/acts/logical_scrapers~linkedin-post-scraper/run-sync-get-dataset-items": {
14 "post": {
15 "operationId": "run-sync-get-dataset-items-logical_scrapers-linkedin-post-scraper",
16 "x-openai-isConsequential": false,
17 "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
18 "tags": [
19 "Run Actor"
20 ],
21 "requestBody": {
22 "required": true,
23 "content": {
24 "application/json": {
25 "schema": {
26 "$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/logical_scrapers~linkedin-post-scraper/runs": {
50 "post": {
51 "operationId": "runs-sync-logical_scrapers-linkedin-post-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/logical_scrapers~linkedin-post-scraper/run-sync": {
93 "post": {
94 "operationId": "run-sync-logical_scrapers-linkedin-post-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 "urls"
135 ],
136 "properties": {
137 "urls": {
138 "title": "URL of the post",
139 "type": "array",
140 "description": "The URL of the post you want to get the data from.",
141 "items": {
142 "type": "string"
143 }
144 }
145 }
146 },
147 "runsResponseSchema": {
148 "type": "object",
149 "properties": {
150 "data": {
151 "type": "object",
152 "properties": {
153 "id": {
154 "type": "string"
155 },
156 "actId": {
157 "type": "string"
158 },
159 "userId": {
160 "type": "string"
161 },
162 "startedAt": {
163 "type": "string",
164 "format": "date-time",
165 "example": "2025-01-08T00:00:00.000Z"
166 },
167 "finishedAt": {
168 "type": "string",
169 "format": "date-time",
170 "example": "2025-01-08T00:00:00.000Z"
171 },
172 "status": {
173 "type": "string",
174 "example": "READY"
175 },
176 "meta": {
177 "type": "object",
178 "properties": {
179 "origin": {
180 "type": "string",
181 "example": "API"
182 },
183 "userAgent": {
184 "type": "string"
185 }
186 }
187 },
188 "stats": {
189 "type": "object",
190 "properties": {
191 "inputBodyLen": {
192 "type": "integer",
193 "example": 2000
194 },
195 "rebootCount": {
196 "type": "integer",
197 "example": 0
198 },
199 "restartCount": {
200 "type": "integer",
201 "example": 0
202 },
203 "resurrectCount": {
204 "type": "integer",
205 "example": 0
206 },
207 "computeUnits": {
208 "type": "integer",
209 "example": 0
210 }
211 }
212 },
213 "options": {
214 "type": "object",
215 "properties": {
216 "build": {
217 "type": "string",
218 "example": "latest"
219 },
220 "timeoutSecs": {
221 "type": "integer",
222 "example": 300
223 },
224 "memoryMbytes": {
225 "type": "integer",
226 "example": 1024
227 },
228 "diskMbytes": {
229 "type": "integer",
230 "example": 2048
231 }
232 }
233 },
234 "buildId": {
235 "type": "string"
236 },
237 "defaultKeyValueStoreId": {
238 "type": "string"
239 },
240 "defaultDatasetId": {
241 "type": "string"
242 },
243 "defaultRequestQueueId": {
244 "type": "string"
245 },
246 "buildNumber": {
247 "type": "string",
248 "example": "1.0.0"
249 },
250 "containerUrl": {
251 "type": "string"
252 },
253 "usage": {
254 "type": "object",
255 "properties": {
256 "ACTOR_COMPUTE_UNITS": {
257 "type": "integer",
258 "example": 0
259 },
260 "DATASET_READS": {
261 "type": "integer",
262 "example": 0
263 },
264 "DATASET_WRITES": {
265 "type": "integer",
266 "example": 0
267 },
268 "KEY_VALUE_STORE_READS": {
269 "type": "integer",
270 "example": 0
271 },
272 "KEY_VALUE_STORE_WRITES": {
273 "type": "integer",
274 "example": 1
275 },
276 "KEY_VALUE_STORE_LISTS": {
277 "type": "integer",
278 "example": 0
279 },
280 "REQUEST_QUEUE_READS": {
281 "type": "integer",
282 "example": 0
283 },
284 "REQUEST_QUEUE_WRITES": {
285 "type": "integer",
286 "example": 0
287 },
288 "DATA_TRANSFER_INTERNAL_GBYTES": {
289 "type": "integer",
290 "example": 0
291 },
292 "DATA_TRANSFER_EXTERNAL_GBYTES": {
293 "type": "integer",
294 "example": 0
295 },
296 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
297 "type": "integer",
298 "example": 0
299 },
300 "PROXY_SERPS": {
301 "type": "integer",
302 "example": 0
303 }
304 }
305 },
306 "usageTotalUsd": {
307 "type": "number",
308 "example": 0.00005
309 },
310 "usageUsd": {
311 "type": "object",
312 "properties": {
313 "ACTOR_COMPUTE_UNITS": {
314 "type": "integer",
315 "example": 0
316 },
317 "DATASET_READS": {
318 "type": "integer",
319 "example": 0
320 },
321 "DATASET_WRITES": {
322 "type": "integer",
323 "example": 0
324 },
325 "KEY_VALUE_STORE_READS": {
326 "type": "integer",
327 "example": 0
328 },
329 "KEY_VALUE_STORE_WRITES": {
330 "type": "number",
331 "example": 0.00005
332 },
333 "KEY_VALUE_STORE_LISTS": {
334 "type": "integer",
335 "example": 0
336 },
337 "REQUEST_QUEUE_READS": {
338 "type": "integer",
339 "example": 0
340 },
341 "REQUEST_QUEUE_WRITES": {
342 "type": "integer",
343 "example": 0
344 },
345 "DATA_TRANSFER_INTERNAL_GBYTES": {
346 "type": "integer",
347 "example": 0
348 },
349 "DATA_TRANSFER_EXTERNAL_GBYTES": {
350 "type": "integer",
351 "example": 0
352 },
353 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
354 "type": "integer",
355 "example": 0
356 },
357 "PROXY_SERPS": {
358 "type": "integer",
359 "example": 0
360 }
361 }
362 }
363 }
364 }
365 }
366 }
367 }
368 }
369}
scrape post from linkedin 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 Post 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: