"A tool for automatically generating LinkedIn posts" matching MCP servers:

Enables AI agents to discover and fetch LinkedIn posts with engagement metrics (reactions, comments, shares) and author details, returning structured JSON per post.

Enables users to read and analyze their own LinkedIn posts and shares using OAuth login and LinkedIn's Member Data Portability API. Supports post listing, analysis, draft matching, and engagement enrichment.

Provides tools for automating LinkedIn job post search and management. Job opportunities often appear in LinkedIn posts first, before they're posted on traditional job boards. By monitoring LinkedIn posts, you can discover opportunities earlier and get a competitive advantage in your job search.

An MCP server that lets AI assistants like Claude read LinkedIn data through your own logged-in browser session. Access profiles and companies, search for jobs, or get job details.

Enables LinkedIn profile reads and post operations through a local-first MCP server, with OAuth token management and approval-friendly tools for OpenWorker.

Enables LLMs to perform addition calculations through a stdio-based MCP server with an add_numbers tool and type-safe validation.

Post to LinkedIn from Claude — create posts, upload images, edit/delete posts, and manage company pages via natural language. Uses the official LinkedIn REST API with OAuth 2.0.

Enables Claude Code users to safely edit their own LinkedIn profile by drafting proposed changes as diffs and requiring explicit human approval before the single write tool applies them.

A Model Context Protocol server that provides a scratchpad tool for LLMs to organize thoughts, take notes, and plan approaches to complex problems.

Enables AI assistants to search LinkedIn jobs and read LinkedIn profiles read-only using a real Chrome session via CDP, with tools for job listings, full job details, profile data, and session management.

A local MCP server that lets Claude log in to LinkedIn and publish image posts to your personal profile feed, backed by LinkedIn's REST Images API and Posts API.

Enables viewing your own LinkedIn account data—such as profile views, applications, saved jobs, job listings, and notifications—as structured tool results, with optional gated write actions for saving or unsaving jobs and unfollowing companies.

A standalone MCP server that exposes typed LinkedIn capabilities (jobs, people, companies, posts, invitations, messaging) through the visible LinkedIn web UI, enabling workflow automation.

MCP server for LinkedIn publishing from AI coding assistants. Dry run by default, SKILL.md for safe workflows, 28 unit tests. MIT licensed.

MCP server that posts to LinkedIn through the LinkedIn API. Enables creating text posts on your LinkedIn profile using natural language from any MCP-compatible client.

Lets AI agents publish posts to personal profiles or administered company pages, comment on posts, list recent posts, and retrieve analytics such as impressions, reactions, comments, shares, and clicks.

Enables AI assistants to access and interact with LinkedIn data—profiles, messaging, jobs, companies, and more—via MCP, with remote or local deployment.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Enables AI agents to publish posts, images, comments, and reactions to LinkedIn as the authenticated user, with built-in safety features like daily budgets and deduplication.

An unofficial Model Context Protocol server enabling AI assistants to access LinkedIn profile data, network connections, search people and jobs, and send messages via OAuth 2.1.