Nexscope

LinkedIn Search Posts

Find public LinkedIn posts and articles by keyword through Google Search. Read available author, text, media, engagement and publication details.

CostAt least 10 credits / call
Try online
POST · https://api.nexscope.ai/social/linkedin/search/postsMCP · social_linkedin_search_posts

What this API does

Find public LinkedIn posts and articles by keyword through Google Search. Read available author, text, media, engagement and publication details. The request accepts query, date_posted, cursor. Its documented result includes platform, resourceStatus.

LinkedIn Search Posts API use cases

Plan a LinkedIn Search Posts request

A researcher checks the published operation description and supplies query, date_posted, cursor for LinkedIn Search Posts. The request stays within the supported parameters rather than assuming other platform capabilities.

Inspect LinkedIn Search Posts results

An analyst reviews platform, resourceStatus from LinkedIn Search Posts for the requested subject. Missing values remain explicit, and the response does not establish complete platform coverage.

Document LinkedIn Search Posts observations

A researcher records the inputs and available results from LinkedIn Search Posts alongside its published description. The record supports a scoped review without inferring unsupported actions, refresh intervals or broader conclusions.

LinkedIn Search Posts API FAQ

What does the LinkedIn Search Posts API return?

Find public LinkedIn posts and articles by keyword through Google Search. Read available author, text, media, engagement and publication details. The documented output includes platform, resourceStatus. It corresponds to the supplied query, date_posted, cursor. Optional fields can be absent; a missing value should not be interpreted as a measured zero. Example values illustrate the response shape, rather than live account results.

How many credits does the LinkedIn Search Posts API cost?

The current documented cost is At least 10 credits / call. This is the same cost shown at the top of this page. If a range or estimate is displayed, the final charge depends on the request. Review your available credits and the pricing page before calling the API, and check API usage records for the actual charge.

How do I call the LinkedIn Search Posts API from my app or an MCP client?

Send a POST request to https://api.nexscope.ai/social/linkedin/search/posts with your API key as a Bearer token and the JSON inputs shown in API integration. In a compatible MCP client such as Claude or Cursor, connect Nexscope and call social_linkedin_search_posts. Use the MCP arguments shown in the MCP guide, or switch Online test to MCP to review its request before adding it to your app.

View plans and creditsConnect this API with MCP

Try this API
Endpoint
https://api.nexscope.ai/social/linkedin/search/posts
MCP method
social_linkedin_search_posts

Step 1 of 3 · Authenticate

Authentication

All run endpoints require a user API key. Send it as a bearer token in the Authorization header.

Authorization: Bearer nk-xxxxxxxxxxxxxxxxx
Missing or invalid API keys return an authentication error. Manage keys from .

Step 2 of 3 · Send a request

POSThttps://api.nexscope.ai/social/linkedin/search/posts

Run an API

Send a JSON request body using the parameters described below.

Example request

Replace YOUR_API_KEY, then run this command in your terminal.

curl -X POST 'https://api.nexscope.ai/social/linkedin/search/posts' \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "query": "ai agents"
}'

Code example

{
  "query": "ai agents"
}

Step 3 of 3 · Inspect the result

Check the response

Read code for the request status and data for the result. Open the parameter and response reference for the full field definitions.

HTTP status codes

CodeDescription
200Default HTTP response for both success and many business errors. Only outer JSON code 0 indicates success or asynchronous acceptance; inspect data for the result.
429Execution admission rate limit; honor Retry-After when present.
503Execution admission is temporarily unavailable; honor Retry-After when present.
Opt-inX-Nexscope-Http-Status: semantic maps controller-handled business errors to HTTP status on run and task routes. Pre-authentication failures, such as a missing API key (code 11209), may still return HTTP 200 before this mapping. Always check the outer JSON code; malformed requests and infrastructure failures may also return non-200 HTTP responses.
All categories/ Social Data
POSThttps://api.nexscope.ai/social/linkedin/search/posts

Run this API

Send a JSON request to execute this API and receive the documented response payload.

Endpoint

MethodPOST
Pathhttps://api.nexscope.ai/social/linkedin/search/posts
AuthBearer API key
Content-Typeapplication/json

Request parameters

NameTypeRequiredDescription
querystringrequired
Keyword or phrase to search for in public LinkedIn posts
Example: ai agents
date_postedstringoptional
Date posted filter based on Google-indexed results
cursorstringoptional
The cursor returned from the previous response. The maximum cursor is 11; cursor 12 or greater returns a 400 response.

Social data contract

Use your Nexscope API key. No supplier credentials are required. Requests reject unknown fields, including pageSize. URLs require HTTPS and an exact supported platform host and resource path. Documented YouTube video URLs may use youtu.be; other short links are unsupported. Check the request schema for supported fields and defaults.

Each request fetches one page. Continue manually with the returned nextCursor, or nextPage for Instagram Reels (pages 1–11). Cursors are opaque, unchanged strings up to 65536 UTF-8 bytes. No automatic pagination, retry, media download or transcription is performed. Repeated requests may purchase data again.

Resource status is independent of HTTP and billing: AVAILABLE, PARTIAL, PRIVATE, RESTRICTED, NOT_FOUND, NO_TRANSCRIPT or UNKNOWN can accompany code 0. Unknown values remain null; arrays remain empty arrays. fetchedAt is the response observation time; sourceFetchedAt is null without source evidence.

usage.billingStatus is NOT_CHARGED, SETTLED or UNKNOWN; chargedCredits is null when unconfirmed. Unknown charges never mean free. Completed lookups have a minimum charge of 10 credits, including cached, no-caption and unavailable-resource results; check API usage records for the actual charge. Parameter errors and unpublished APIs use the standard error envelope; upstream failures use code 13007, rate limits 429 and timeouts 408. Always check code and msg.

Response example

Platform response envelope. code 0 indicates success or acceptance; data contains the business result.

{
  "code": 0,
  "cost": "-1",
  "data": {
    "data": {
      "cursor": "2",
      "posts": [
        {
          "author": {
            "followers": 313422,
            "image": "https://media.licdn.com/dms/image/v2/D5603AQGl7mUqMgCLRQ/profile-displayphoto-scale_200_200/B56Z3V9cKNKgAc-/0/1777411150180?e=2147483647&v=beta&t=oVB3kzDdrFGH-2pOYeziFk3m_B8fTCiH190YbTMrgoY",
            "name": "Aakash Gupta",
            "url": "https://www.linkedin.com/in/aagupta"
          },
          "commentCount": 25,
          "comments": [
            {
              "author": "Lewin Wanzer",
              "datePublished": "2025-08-02T01:23:21.112Z",
              "id": "7357219423591563264",
              "linkedinUrl": "https://www.linkedin.com/in/lewinwanzer",
              "publishedTimeAgo": "1y",
              "reactionCount": 0,
              "text": "Thanks for sharing, Aakash. Appreciate the breakdown—but here’s the twist most are missing: the AI agent is Agent Smith.\nThe more we chase “smart tasks” without structure, the more we lose the plot. Developers are confused. “AI Architects” don’t exist. And agents are now doing things they were never cleared to do.\nWe don’t need more tools—we need orchestration, identity-bound execution, and governed outcomes. Tourque will set the standard. Until that’s the norm, it’s just hype on autopilot.",
              "urn": "urn:li:comment:(urn:li:ugcPost:7354600336214376448,7357219423591563264)"
            }
          ],
          "datePublished": "2025-07-25T19:56:02.566Z",
          "description": "There's way too much hype about AI agents.\n\nHere's your simple guide:\n\nForget the super complex taxonomies out there. There are 4 categories of tools you should know.\n\n1. Consumer Agents\n\nThe latest LLMs, like Grok and Claude, have agents built-in. ChatGPT is rolling out the 'Agent' tool to paid plans as we speak.\n\nThese are best for:\n\n- Ad-hoc analysis\n- Quick research tasks\n- Content creation (PRDs, strategy docs)\n\n2. No-Code Agent Builders\n\nThere is a new class of tools that you must know. Tools like Zapier and Lindy offer where you can do things like connecting your Gmail to Claude.\n\nBe sure to explore these for:\n\n- Email triage\n- Competitor monitoring\n- Automated data reporting\n\n3. Developer-First Platforms\n\nAll the tools you've heard like CrewAI, Langchain, and Autogen are great frameworks for developers. Think of them as the React/Node for agents.\n\nThey're for:\n\n- Customer-facing agents\n- Deep system integrations\n- Complex, proprietary business logic\n\n4. Specialized Agent Apps\n\nTools like Cursor, Otter, and Jasper are specialized agent apps. They're supported by complex business logic to do one task really well.\n\nMy recommendations:\n\n- Coding → Cursor\n- Meetings → Otter AI\n- Research → Perplexity\n\nReady to go the layer deeper? I teamed up with AI PM at Meta Vikash Rungta to write you the web's most practical and simple guide: https://lnkd.in/eeey5Cxr\n\nPlease, let's end all the hype and talk real use cases.\n\nP.S. What agent are you using most?",
          "image": "https://media.licdn.com/dms/image/v2/D4E1FAQHAzpgC7eaKgw/feedshare-document-images_160/B4EZhDHPPEGoAs-/1/1753472629037?e=1780531200&v=beta&t=7UAmCkScn1TSkvHB9HxLTPoBV7wibupD2WlKSec3ork",
          "images": [
            "https://media.licdn.com/dms/image/v2/D4E1FAQHAzpgC7eaKgw/feedshare-document-images_160/B4EZhDHPPEGoAs-/1/1753472629037?e=1780531200&v=beta&t=7UAmCkScn1TSkvHB9HxLTPoBV7wibupD2WlKSec3ork"
          ],
          "likeCount": 217,
          "media": "https://media.licdn.com/dms/image/v2/D4E1FAQHAzpgC7eaKgw/feedshare-document-images_160/B4EZhDHPPEGoAs-/1/1753472629037?e=1780531200&v=beta&t=7UAmCkScn1TSkvHB9HxLTPoBV7wibupD2WlKSec3ork",
          "url": "https://www.linkedin.com/posts/aagupta_what-you-need-to-know-ai-agents-activity-7354600338621906944-RvXR"
        }
      ],
      "query": "ai agents",
      "success": true
    },
    "platform": "linkedin",
    "resourceStatus": "AVAILABLE",
    "usage": {
      "billingStatus": "UNKNOWN"
    }
  },
  "msg": null,
  "time": "2026-01-01 00:00:00",
  "traceId": null,
  "ts": "0"
}

Response fields

NameTypeRequiredDescription
codeintegerrequired
0 means accepted or successful; nonzero is a platform error.
coststringrequired
Elapsed milliseconds, never credits; -1 outside web requests.
dataanyrequired
Data value used by this API operation.
msgstring | nullrequired
Msg value used by this API operation.
timestringrequired
Server local time: yyyy-MM-dd HH:mm:ss.
traceIdstring | nullrequired
Trace id value used by this API operation.
tsstringrequired
Epoch milliseconds.

Any of option 1 — requires platform, resourceStatus, data, usage

NameTypeRequiredDescription
dataobjectrequired
Data value used by this API operation.
data.dataobjectrequired
Data value used by this API operation.
data.platformstringrequired
Platform value used by this API operation.
data.resourceStatusstringrequired
Resource status value used by this API operation.
data.usageobjectrequired
Usage value used by this API operation.

Any of option 2

NameTypeRequiredDescription
datanullrequired
Data value used by this API operation.

Responses

CodeDescription
200Default HTTP response for both success and many business errors. Only outer JSON code 0 indicates success or asynchronous acceptance; inspect data for the result.
429Execution admission rate limit; honor Retry-After when present.
503Execution admission is temporarily unavailable; honor Retry-After when present.
Opt-inX-Nexscope-Http-Status: semantic maps controller-handled business errors to HTTP status on run and task routes. Pre-authentication failures, such as a missing API key (code 11209), may still return HTTP 200 before this mapping. Always check the outer JSON code; malformed requests and infrastructure failures may also return non-200 HTTP responses.

Data source, freshness, and limitations

Source, freshness, coverage, rate limits, and estimation notes are not specified in this API definition unless they appear in the request or response field documentation above. Do not assume official marketplace data or real-time freshness when it is not explicitly documented.

Step 1 of 2 · Connect your MCP client

MCP

V2 recommended

Connect remote agents through the standard MCP 2025-11-25 Streamable HTTP endpoint. Use OAuth 2.1 Authorization Code with PKCE, or an API key for compatibility.

POST https://api.nexscope.ai/mcp
MCP-Protocol-Version: 2025-11-25
Content-Type: application/json
Authentication

OAuth clients request the mcp:tools scope. The endpoint's 401 response advertises protected-resource metadata for authorization discovery.

Step 2 of 2 · Call the tool

Call a tool

{
  "jsonrpc": "2.0",
  "id": "tool-call-1",
  "method": "tools/call",
  "params": {
    "name": "social_linkedin_search_posts",
    "arguments": {
      "query": "ai agents"
    }
  }
}

Legacy MCP v1

Existing API-key clients can continue using the compatibility endpoint. New integrations should use MCP v2.

GET / POST /mcp/legacy

What can you do with this API?

Data explained and practical use cases

AI Guide

Question

What data can LinkedIn Search Posts provide, and how might I use it?

AI answer

Finds public LinkedIn posts, feed updates, and Pulse articles by keyword using Google Search, then returns post details such as description, author, media, images, like count, comment count, and published date when LinkedIn exposes them publicly. Results depend on what Google has indexed, so this is best-effort and not a complete LinkedIn-native search. Use date_posted for recent posts and pass the returned cursor to fetch the next page. Cursors are limited to pages 1 through 11; cursor 12 or

Data categoryDocumented fieldsHow to use them
Requestquery, cursor, date_postedProvide the required identifiers, filters, or paging inputs listed in the API document.
Responsedata.data, data.platform, data.resourceStatusInspect returned values and source references; availability depends on the request and upstream source.
  • Review LinkedIn Search Posts.
    • Prompt example: “Retrieve LinkedIn Search Posts for [search phrase]. Summarize only the information actually returned and preserve source links when available. Report private, restricted, missing or partial results explicitly; missing values are not zero.”
  • Collect a Bounded Set of Results.
    • Prompt example: “Retrieve LinkedIn Search Posts for [search phrase] across at most two pages within my approved credit budget. Use only the continuation information actually returned, with the same query and filters. Stop at the documented page limit, an absent continuation, an end indicator or a repeated page. Keep source references and report that the collection is bounded, not exhaustive.”
  • Focus the Review on a Selected Period.
    • Prompt example: “Retrieve LinkedIn Search Posts for [search phrase] for [a period supported by this tool]. Use the documented date meaning, format and limits, and show that scope with the results. Keep required date pairs together. Do not treat a search-index window as an exact publication-time filter or infer a complete historical archive.”
  • Prepare a Snapshot of Returned Public Counts.
    • Prompt example: “Retrieve LinkedIn Search Posts for [search phrase] and make a compact table of the public counts actually returned. Keep each count attached to its item or account, label estimates and preserve the observation time when supplied. Do not invent engagement rates, historical growth, unique audience size or missing values.”

These are suggested workflows, not completed lookups. Report missing, restricted, or partial data explicitly; verify the live response before making a decision.

Online test

Execute the current API with your API key and JSON payload. Online tests use this site's configured API environment; the Endpoint and copyable examples use the public integration address.

One request fetches one page. Copy nextCursor into cursor, or nextPage into page (1–11 for Reels), then run manually. Repeated requests may purchase data again. Completed lookups have a minimum charge of 10 credits, including cached, no-caption, private, restricted and not-found results. Resource status and actual billing status are independent; null credits are unknown, never free. Check usage.billingStatus, usage.chargedCredits and API usage records for the actual charge.

Try it

Send a real request with the same contract shown in the reference.

Endpoint
/social/linkedin/search/posts
MCP method
social_linkedin_search_posts
cURL
curl -X POST \
  https://api.nexscope.ai/social/linkedin/search/posts \
  -H "Authorization: Bearer nk-..." \
  -H "Content-Type: application/json" \
  -d '{ "query": "ai agents" }'
Request estimate: Estimating…Usage based. The final charge depends on actual usage. Estimating does not run the API or charge credits.API usage records
Response
No response yet. Run the request to see the response here.

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