LinkedIn Posts Search Scraper

The fastest, lightest way to collect LinkedIn posts on Apify. Turn any topic, profile, or post link into clean, structured JSON — ready for dashboards, alerts, research, and AI workflows. Results land in your dataset in real time, as each post is collected.

Built for marketers, founders, sales teams, researchers, and builders who need reliable LinkedIn post data at scale — without heavy setups, slow runs, or messy exports.

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Why this Actor

	LinkedIn Posts Search Scraper	Typical post collector
Speed	~1–3 s per post	5–15 s per post
Memory	256–512 MB default	2–4 GB+
Setup	Run in seconds — no login	Often requires accounts & maintenance
Cost	Low compute, efficient runs	High
Output	Structured JSON, LLM-ready	Often messy HTML
Scale	Up to 1,000 posts per keyword	Often capped lower
Filters	Keyword, author, company, topic, date, sort	Often keyword-only

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What you get — every post, fully structured

Each record is one LinkedIn post with featureType: "post" and scrapedAt so you can sort, filter, and join with your own data.

Field	What it tells you
text, authorName, authorHeadline, authorUrl	Post content and who published it
numLikes, numComments, numShares, numReactions	Engagement at a glance
createdAtISO, postUrl, urn	When it was posted and direct links
comments[]	Top comments — author, text, likes
mediaUrls[], articleTitle, articleUrl	Images, videos, and shared articles
searchQuery, sourceProfile	Which search or profile produced this row

Set includeRaw: true if you need the extended source payload for custom processing.

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Three ways to collect posts

By keyword (default)

Search LinkedIn content the way you would on the platform:

• Keywords — one search per keyword (e.g. AI regulation, product launch, hiring freeze)
• Location — narrow by geography
• Author — filter by person name
• Company — posts from or about a company
• Topic — combine with keywords for sharper results
• Date posted — any time, past month, week, or 24 hours
• Sort — relevance or most recent
• Volume — up to 1,000 posts per keyword

By post URL

Paste LinkedIn post or activity links and get structured data back instantly.

By profile URL

Load recent posts from any public profile's activity — great for tracking executives, competitors, or influencers.

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Use cases — real outcomes

• Social listening — track brand mentions, product launches, and industry conversations
• Competitive intelligence — monitor what competitors and leaders are saying
• Sales & BD — spot buying signals, funding news, and hiring announcements in posts
• Content research — study what topics and formats get engagement in your niche
• Influencer & executive tracking — follow key profiles and export their latest posts
• PR & comms — collect posts around a crisis, campaign, or news event
• AI assistants & agents — summarize trends, draft replies, score sentiment, or build briefings
• Data warehouses & CRMs — push JSON into Snowflake, BigQuery, HubSpot, Airtable, or your stack via API

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LLM & MCP integration

Output is structured JSON — ideal for ChatGPT, Claude, Gemini, LangChain, LlamaIndex, CrewAI, and custom agents. No cleanup step. No HTML stripping. Just records your model can read.

Recommended workflow

1. Run the Actor with your keywords, URLs, or profiles.
2. Pull dataset items via Apify API, webhook, or export JSON/CSV.
3. Pass records to your LLM, vector store, or automation — one post per row.

Example: one post record for an LLM prompt

{
  "featureType": "post",
  "authorName": "Jane Doe",
  "authorHeadline": "VP Marketing at Acme",
  "authorUrl": "https://www.linkedin.com/in/janedoe",
  "text": "Excited to share that Acme just launched our new AI platform...",
  "numLikes": 342,
  "numComments": 48,
  "numShares": 12,
  "createdAtISO": "2026-07-06T10:00:00.000Z",
  "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:1234567890/",
  "comments": [
    {
      "author": "John Smith",
      "text": "Congrats on the launch!",
      "likes": 5
    }
  ],
  "searchQuery": "AI platform launch",
  "scrapedAt": "2026-07-08T12:00:00.000Z"
}

Apify MCP (Model Context Protocol)

Connect the Apify MCP server so AI assistants can:

• Run this Actor from natural-language instructions
• Read post results directly in the chat
• Chain with other Actors — enrich contacts, send alerts, update spreadsheets

Example MCP conversation:

User: "Find 30 posts about AI regulation from the past week and summarize top themes"

→ MCP runs LinkedIn Posts Search Scraper with postKeywords, postDatePosted=week
→ MCP reads dataset items
→ LLM summarizes trending topics and key voices

API quick start

curl -X POST "https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "postSearchMode": "keyword",
    "postKeywords": ["AI regulation"],
    "postDatePosted": "week",
    "postsPerQuery": 30,
    "includeComments": true
  }'

Fetch results: GET https://api.apify.com/v2/datasets/{datasetId}/items?format=json

Dataset views in Apify Console: Overview (core fields) · Full details (includes media and traceability)

Export as JSON, CSV, Excel, RSS, or via API.

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Input reference

Input	Type	Default	Description
postSearchMode	enum	keyword	keyword, url, or profile
postKeywords	string[]	["AI regulation"]	Search keywords — one run per keyword
postLocation	string	"United States"	Geographic filter
postAuthor	string	""	Author name filter
postCompany	string	""	Company filter
postTopic	string	""	Topic or theme filter
postDatePosted	enum	any	any, month, week, day
postSort	enum	relevance	relevance or date
postsPerQuery	integer	10	Max posts per keyword (1–1000)
postUrls	string[]	example post URL	Post URLs (url mode)
activityProfiles	string[]	example profile URL	Profile URLs or handles (profile mode)
postsPerProfile	integer	10	Max posts per profile (1–500)
includeComments	boolean	true	Include top comments on each post
maxItems	integer	25	Global cap on total posts
includeRaw	boolean	false	Attach extended source payload
proxyConfiguration	object	residential US	Connection settings (US residential recommended)

Full schema: Input tab on Apify Console or .actor/input_schema.json in this repository.

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Output reference

Every dataset row is a single post. All rows include featureType: "post" and scrapedAt.

Field	Type	Description
featureType	string	Always "post"
scrapedAt	string	ISO timestamp when the row was collected
text	string | null	Post body text
authorName	string | null	Author display name
authorHeadline	string | null	Author headline or role
authorUrl	string | null	Author profile or company URL
authorType	string | null	Author type when available
postUrl	string | null	Direct link to the post
urn	string | null	LinkedIn activity identifier
createdAtISO	string | null	When the post was published
numLikes	integer | null	Like count
numComments	integer | null	Comment count
numShares	integer | null	Share count
numReactions	integer | null	Total reactions when available
mediaType	string | null	Media type (e.g. image, video)
mediaUrls	string[]	Attached image or video URLs
articleTitle	string | null	Linked article title
articleUrl	string | null	Linked article URL
sharedContentUrl	string | null	Shared link URL when present
comments	object[]	Top comments: author, authorUrl, text, likes
searchQuery	string | null	Keyword that produced this row
sourceProfile	string | null	Profile handle (profile mode)
raw	object	Extended payload (when includeRaw is true)

Full schema: Dataset tab on Apify Console or .actor/dataset_schema.json in this repository.

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Quick start examples

Topic monitoring — past week

{
  "postSearchMode": "keyword",
  "postKeywords": ["AI regulation", "EU AI Act"],
  "postDatePosted": "week",
  "postSort": "date",
  "postsPerQuery": 50,
  "includeComments": true
}

Posts from a specific company

{
  "postSearchMode": "keyword",
  "postKeywords": ["product launch"],
  "postCompany": "Stripe",
  "postsPerQuery": 25
}

Track an executive's recent posts

{
  "postSearchMode": "profile",
  "activityProfiles": ["https://www.linkedin.com/in/janedoe"],
  "postsPerProfile": 30,
  "includeComments": false
}

Collect specific post URLs

{
  "postSearchMode": "url",
  "postUrls": [
    "https://www.linkedin.com/feed/update/urn:li:activity:1234567890/"
  ],
  "includeComments": true
}

High-volume industry scan

{
  "postSearchMode": "keyword",
  "postKeywords": ["generative AI", "LLM", "machine learning"],
  "postLocation": "United States",
  "postsPerQuery": 500,
  "maxItems": 1500,
  "includeComments": true
}

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Performance & reliability

• Lightweight by design — default 512 MB memory handles large runs with multiple keywords.
• Fast collection — posts stream into your dataset as they are found; no waiting until the end.
• Residential proxy (US recommended) — best results and consistent throughput on LinkedIn.
• Smart coverage — automatically widens search when you request large result sets.

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Limitations & compliance

• This is an unofficial tool — not affiliated with LinkedIn.
• Use responsibly and comply with applicable laws and LinkedIn's Terms of Service.
• Some fields (engagement counts, comments) appear only when publicly visible.
• Post availability can change; removed or restricted posts may not return data.

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Contact & custom work

Need something beyond this Actor? I design and build custom data solutions and full-stack products for teams that want results — not experiments.

Email: dubem115@gmail.com
GitHub: github.com/DrunkCodes

Reach out for:

• Custom Apify Actors — any website, social platform, or API
• LinkedIn & social data projects — listening pipelines, alerts, and dashboards at scale
• LLM & MCP integrations — connect your data to ChatGPT, Claude, and agent workflows
• Web apps & automation — data tools, internal platforms, SaaS products, and client-facing apps

Whether you need a one-off data feed or a production system, I can help you ship it.

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LinkedIn Posts Search Scraper · by DrunkCodes