"A tool for publishing or running 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.

Provides AI agents with real-time ground truth about what's actually running on the machine, including live agent sessions, listening TCP ports, loaded daemons, and system stats. It reads directly from the OS via fixed commands, ensuring agents never rely on stale docs or transcripts.

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

Connects AI clients to a personal Intervals.icu account to retrieve recent running activities as clean, normalized JSON. It supports read-only lookups filtered by number of runs and how many days back to search.

MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

Enables conversational analysis of n8n workflows and Make scenarios for silent-failure risks, with tools to explain findings, compare workflow versions, and list rules.

Enables AI assistants to publish text, link, and image posts to a personal LinkedIn profile, as well as comment, react, and delete posts, through the official LinkedIn API.

Provides comprehensive running performance calculations including VDOT, training paces, race time predictions, velocity markers, and heart rate zones using Jack Daniels, Greg McMillan, and Riegel methodologies.

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

Enables secure LinkedIn OAuth connection and publishing of text and single-image posts with explicit human approval before anything goes live.

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 publishing and scheduling LinkedIn posts through the official API, with content calendar and post brief tools for consistent growth.

Enables full control over LinkedIn profiles through browser automation, allowing reading, editing, adding, removing entries, and publishing posts directly from conversations.

Provides live wait times and office details for all 60 Oregon DMV field offices by scraping the ODOT website, with no authentication required.

Enables publishing explicitly approved text posts to LinkedIn and checking connection status via a stateless MCP connector.

Enables publishing to LinkedIn from a Second Brain using four tools and the official API, with a handbrake that requires confirmation before posting and supports deleting posts.

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.