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  1. Home
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  3. MCP Linkedin
MCP Linkedin logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 3:45:59 PM

MCP Linkedin

User RatingsBe the first to rate and review this MCP server!
View Repository2 GitHub StarsTotal stargazers on GitHub for the source repository (2 stars).Visit Website
linkedinsocial-mediapublishingunipile

Publishes LinkedIn posts, comments, and reactions through Unipile with preview-first safeguards.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

One-click editor setup isn’t available for this listing yet β€” we don’t have a confirmed install command, and we’d rather show nothing than point your editor at the wrong package or host. Follow the project’s own setup instructions, linked above.

Manual Client & Custom JSON ConfigExpand JSON β–Ύ
No confirmed setup config for this listing yet. We only publish a config block when the install details come from the project itself β€” its README, its docs, or a verified owner. We haven’t found those for timkulbaev/mcp-linkedin, and we’d rather show nothing than a guess you’d paste into your client. Follow the project’s own setup instructions for the current steps.
Install Directory Badge Claim listing Alternatives🌐 More in Social Media

Overview

The timkulbaev/mcp-linkedin MCP server exposes LinkedIn publishing, commenting, and reactions through the Unipile API. It runs over MCP's stdio transport and uses Unipile credentials supplied through environment variables. Publishing and commenting default to dry-run previews, while reactions execute immediately. Reach for it when an AI workflow needs to prepare and selectively publish LinkedIn content, including media and company mentions.

Use cases

β€’Draft and preview LinkedIn posts before publishing
β€’Publish posts with image or video attachments
β€’Add comments to LinkedIn posts
β€’React to LinkedIn posts with supported reaction types
β€’Mention companies in generated LinkedIn content

Key features

β€’LinkedIn post publishing through Unipile
β€’Dry-run previews for posts and comments
β€’Comments and immediate reactions
β€’Local or URL-based media attachments
β€’Company mention resolution

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Linkedin.

Extracted Tool Capabilities
LinkedIn post publishing through Unipile
Dry-run previews for posts and comments
Comments and immediate reactions
Local or URL-based media attachments
Company mention resolution

How MCP Linkedin works

What timkulbaev/mcp-linkedin MCP server does

The timkulbaev/mcp-linkedin MCP server gives MCP-compatible AI clients three LinkedIn actions: create an original post, add a comment to an existing post, and react to a post. The server sends these requests to Unipile, which connects the configured LinkedIn account and handles LinkedIn OAuth.

Post creation accepts text, optional media, company mentions, and a dry-run flag. Text is limited to 3,000 characters. Media can be supplied as local paths or URLs, and supported formats include JPG, JPEG, PNG, GIF, WEBP, and MP4. Company names are resolved through Unipile's LinkedIn company search so they can become clickable mentions.

How it works

An MCP client communicates with the local process using JSON-RPC over stdio. The server validates tool inputs, prepares media and mentions, then calls the Unipile API. For remote media URLs, files are downloaded to a temporary directory and removed after the publish attempt.

The intended publishing sequence is preview first, publish second. linkedin_publish and linkedin_comment use dry_run: true by default. A preview reports the proposed content, character count, media validation, resolved mentions, and warnings. The client must call the tool again with dry_run: false to perform the action. linkedin_react has no preview mode and acts immediately.

After a successful post, the response includes a post ID and indicates that the post was automatically liked. A LinkedIn feed URL can be formed from that ID using the activity URN format shown by the project.

Setup and configuration

To run timkulbaev/mcp-linkedin, use Node.js 18 or later. Clone the repository, change into its directory, and run npm install. Configure the MCP client to start index.js with Node and provide an absolute path to that entry point.

Two environment variables are required:

  • UNIPILE_API_KEY: the API key from the Unipile dashboard.
  • UNIPILE_DSN: the Unipile data source name, such as an apiXX.unipile.com:XXXXX value.

The credentials are passed in the MCP client configuration and read from process.env when the process starts; the README does not use a .env file. Before connecting the server, create a Unipile account, connect a LinkedIn account, and retrieve the API key and DSN from the dashboard. Restart Claude Code or Claude Desktop after changing the MCP configuration.

Tools and capabilities

The available tools are:

  • linkedin_publish: previews or publishes an original post, with optional media and company mentions.
  • linkedin_comment: previews or posts a comment using a LinkedIn post URL or raw post URN.
  • linkedin_react: applies like, celebrate, support, love, insightful, or funny to a LinkedIn post.

The media handler checks that local files exist, are non-empty, and use a supported type. Unresolved company names remain visible as preview warnings, and the post may still be published without those mentions.

Limitations and notes

The timkulbaev/mcp-linkedin MCP server requires an active Unipile account connected to LinkedIn; it does not manage LinkedIn credentials directly. Reactions are not protected by dry-run mode, so they should be treated as immediate operations. URL media is temporary and is cleaned up after publishing succeeds or fails.

The repository includes unit tests using Node's built-in test runner and a Biome lint script. The documented client examples cover Claude Code and Claude Desktop, while the server is described as usable with other MCP-compatible clients.

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
2
Stargazers on the source repository.
Directory activity
5 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about MCP Linkedin

Clone the repository, run `npm install` in its directory, and configure the MCP client to start its `index.js` entry point with Node.js 18 or later.

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Technical Specs & Signals

Category🌐Social Media
PricingFree
More technical detailsExpand β–Ύ
AuthAPI key
LicenseMIT
ClientsClaude Desktop
Last updatedSep 3, 2026
Views5
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars2
GitHub Star CountTotal stargazers on GitHub representing community popularity (2 stars).
43Quality signal: Fair Β· 43/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools19/30
Adoption & activity2/15
Community engagement1/10

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