Linkedin Post Comments,Replies,Engagements Scraper | No Cookies
Pricing
$5.00 / 1,000 results
Go to Store
Linkedin Post Comments,Replies,Engagements Scraper | No Cookies
apimaestro/linkedin-post-comments-replies-engagements-scraper-no-cookies
Scrape in Batch all LinkedIn post related data including comments, stats, , reactions, replies and media attachments
5.0 (1)
Pricing
$5.00 / 1,000 results
3
Monthly users
44
Runs succeeded
>99%
Response time
4.7 hours
Last modified
16 days ago
You can access the Linkedin Post Comments,Replies,Engagements Scraper | No Cookies programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
1{
2 "openapi": "3.0.1",
3 "info": {
4 "version": "0.1",
5 "x-build-id": "KfOMogNQiTYuR8UpY"
6 },
7 "servers": [
8 {
9 "url": "https://api.apify.com/v2"
10 }
11 ],
12 "paths": {
13 "/acts/apimaestro~linkedin-post-comments-replies-engagements-scraper-no-cookies/run-sync-get-dataset-items": {
14 "post": {
15 "operationId": "run-sync-get-dataset-items-apimaestro-linkedin-post-comments-replies-engagements-scraper-no-cookies",
16 "x-openai-isConsequential": false,
17 "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
18 "tags": [
19 "Run Actor"
20 ],
21 "requestBody": {
22 "required": true,
23 "content": {
24 "application/json": {
25 "schema": {
26 "$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/apimaestro~linkedin-post-comments-replies-engagements-scraper-no-cookies/runs": {
50 "post": {
51 "operationId": "runs-sync-apimaestro-linkedin-post-comments-replies-engagements-scraper-no-cookies",
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/apimaestro~linkedin-post-comments-replies-engagements-scraper-no-cookies/run-sync": {
93 "post": {
94 "operationId": "run-sync-apimaestro-linkedin-post-comments-replies-engagements-scraper-no-cookies",
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 "postIds"
135 ],
136 "properties": {
137 "postIds": {
138 "title": "Post URLs or IDs",
139 "minItems": 1,
140 "maxItems": 100,
141 "uniqueItems": true,
142 "type": "array",
143 "description": "List of LinkedIn post identifiers. You can use any of these formats:\n- Numeric post IDs (e.g., '7289521182721093633')\n- Activity URLs (e.g., 'https://www.linkedin.com/posts/satyanadella_mayo-clinic-accelerates-personalized-medicine-activity-7285003244957773826-TrmI')\n- Full post URLs (e.g., 'https://www.linkedin.com/posts/ajjames_why-hasnt-the-us-created-an-lvmh-style-luxury-activity-7302346926123798528-dMnz')\n- Comma-separated values will be split automatically",
144 "items": {
145 "type": "string"
146 }
147 },
148 "sortOrder": {
149 "title": "Sort order",
150 "enum": [
151 "most relevant",
152 "most recent"
153 ],
154 "type": "string",
155 "description": "How comments should be sorted",
156 "default": "most relevant"
157 },
158 "limit": {
159 "title": "Result limit per post",
160 "minimum": 1,
161 "maximum": 100,
162 "type": "integer",
163 "description": "Optional: Limit the number of comments returned per post (1-100)",
164 "default": 100
165 }
166 }
167 },
168 "runsResponseSchema": {
169 "type": "object",
170 "properties": {
171 "data": {
172 "type": "object",
173 "properties": {
174 "id": {
175 "type": "string"
176 },
177 "actId": {
178 "type": "string"
179 },
180 "userId": {
181 "type": "string"
182 },
183 "startedAt": {
184 "type": "string",
185 "format": "date-time",
186 "example": "2025-01-08T00:00:00.000Z"
187 },
188 "finishedAt": {
189 "type": "string",
190 "format": "date-time",
191 "example": "2025-01-08T00:00:00.000Z"
192 },
193 "status": {
194 "type": "string",
195 "example": "READY"
196 },
197 "meta": {
198 "type": "object",
199 "properties": {
200 "origin": {
201 "type": "string",
202 "example": "API"
203 },
204 "userAgent": {
205 "type": "string"
206 }
207 }
208 },
209 "stats": {
210 "type": "object",
211 "properties": {
212 "inputBodyLen": {
213 "type": "integer",
214 "example": 2000
215 },
216 "rebootCount": {
217 "type": "integer",
218 "example": 0
219 },
220 "restartCount": {
221 "type": "integer",
222 "example": 0
223 },
224 "resurrectCount": {
225 "type": "integer",
226 "example": 0
227 },
228 "computeUnits": {
229 "type": "integer",
230 "example": 0
231 }
232 }
233 },
234 "options": {
235 "type": "object",
236 "properties": {
237 "build": {
238 "type": "string",
239 "example": "latest"
240 },
241 "timeoutSecs": {
242 "type": "integer",
243 "example": 300
244 },
245 "memoryMbytes": {
246 "type": "integer",
247 "example": 1024
248 },
249 "diskMbytes": {
250 "type": "integer",
251 "example": 2048
252 }
253 }
254 },
255 "buildId": {
256 "type": "string"
257 },
258 "defaultKeyValueStoreId": {
259 "type": "string"
260 },
261 "defaultDatasetId": {
262 "type": "string"
263 },
264 "defaultRequestQueueId": {
265 "type": "string"
266 },
267 "buildNumber": {
268 "type": "string",
269 "example": "1.0.0"
270 },
271 "containerUrl": {
272 "type": "string"
273 },
274 "usage": {
275 "type": "object",
276 "properties": {
277 "ACTOR_COMPUTE_UNITS": {
278 "type": "integer",
279 "example": 0
280 },
281 "DATASET_READS": {
282 "type": "integer",
283 "example": 0
284 },
285 "DATASET_WRITES": {
286 "type": "integer",
287 "example": 0
288 },
289 "KEY_VALUE_STORE_READS": {
290 "type": "integer",
291 "example": 0
292 },
293 "KEY_VALUE_STORE_WRITES": {
294 "type": "integer",
295 "example": 1
296 },
297 "KEY_VALUE_STORE_LISTS": {
298 "type": "integer",
299 "example": 0
300 },
301 "REQUEST_QUEUE_READS": {
302 "type": "integer",
303 "example": 0
304 },
305 "REQUEST_QUEUE_WRITES": {
306 "type": "integer",
307 "example": 0
308 },
309 "DATA_TRANSFER_INTERNAL_GBYTES": {
310 "type": "integer",
311 "example": 0
312 },
313 "DATA_TRANSFER_EXTERNAL_GBYTES": {
314 "type": "integer",
315 "example": 0
316 },
317 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
318 "type": "integer",
319 "example": 0
320 },
321 "PROXY_SERPS": {
322 "type": "integer",
323 "example": 0
324 }
325 }
326 },
327 "usageTotalUsd": {
328 "type": "number",
329 "example": 0.00005
330 },
331 "usageUsd": {
332 "type": "object",
333 "properties": {
334 "ACTOR_COMPUTE_UNITS": {
335 "type": "integer",
336 "example": 0
337 },
338 "DATASET_READS": {
339 "type": "integer",
340 "example": 0
341 },
342 "DATASET_WRITES": {
343 "type": "integer",
344 "example": 0
345 },
346 "KEY_VALUE_STORE_READS": {
347 "type": "integer",
348 "example": 0
349 },
350 "KEY_VALUE_STORE_WRITES": {
351 "type": "number",
352 "example": 0.00005
353 },
354 "KEY_VALUE_STORE_LISTS": {
355 "type": "integer",
356 "example": 0
357 },
358 "REQUEST_QUEUE_READS": {
359 "type": "integer",
360 "example": 0
361 },
362 "REQUEST_QUEUE_WRITES": {
363 "type": "integer",
364 "example": 0
365 },
366 "DATA_TRANSFER_INTERNAL_GBYTES": {
367 "type": "integer",
368 "example": 0
369 },
370 "DATA_TRANSFER_EXTERNAL_GBYTES": {
371 "type": "integer",
372 "example": 0
373 },
374 "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
375 "type": "integer",
376 "example": 0
377 },
378 "PROXY_SERPS": {
379 "type": "integer",
380 "example": 0
381 }
382 }
383 }
384 }
385 }
386 }
387 }
388 }
389 }
390}Linkedin Post Comments,Replies,Engagements 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 Post Comments,Replies,Engagements Scraper | No Cookies 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:
Linkedin Post Comments,Replies,Engagements Scraper | No Cookies API in Python
Linkedin Post Comments,Replies,Engagements Scraper | No Cookies API in JavaScript
Linkedin Post Comments,Replies,Engagements Scraper | No Cookies API through CLI
Linkedin Post Comments,Replies,Engagements Scraper | No Cookies API
Pricing
Pricing model
Pay per resultThis Actor is paid per result. You are not charged for the Apify platform usage, but only a fixed price for each dataset of 1,000 items in the Actor outputs.
Price per 1,000 items
$5.00
![Linkedin Profile Posts [NO COOKIES] avatar](https://images.apifyusercontent.com/_Slv92yHj0i5IpenJQio3CYRTf7K0I0n3H4P07b0GyQ/rs:fill:76:76/cb:1/aHR0cHM6Ly9hcGlmeS1pbWFnZS11cGxvYWRzLXByb2QuczMudXMtZWFzdC0xLmFtYXpvbmF3cy5jb20vdFhKaEQ5SFNvdTY4N2NEUTQtYWN0b3ItTFFRSVhOOU90aGY4ZjdSNW4tRTRIaDRTelRoci02MTEwOS5wbmc.webp){kind=avatar}
