"Searching for someone named Prajwal on LinkedIn" matching MCP servers:

Generates deterministic, reviewable drafts of source-available named-exclusion licenses with SPDX identifiers and digests, without modifying files or performing external actions.

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

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.

Provides an MCP server that tracks open loops (pending decisions or replies) across email, agent sessions, and other channels, enabling agents to query what is waiting on whom.

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.

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 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.

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

Enables AI agents to publish text and link posts, comment, react, and delete posts on LinkedIn through the official OAuth API, with every write gated behind human approval via a two-phase prepare/execute flow. Includes exact-match digests, single-use expiring proposals, daily write caps, and private local token storage with zero third-party dependencies.

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.

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.

Enables LinkedIn API integration for managing profiles, posts, feed, connections, and sending messages through MCP-compatible clients.

Enables MCP-capable agents to read and update a LinkedIn profile, check and publish posts through the official LinkedIn API. Includes a built-in quality gate that blocks drafts reading as machine-generated before anything reaches the public feed.

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

Enables AI assistants to read a member's own LinkedIn data — profile, connections, messages, posts, and other snapshot domains — through LinkedIn's Member Data Portability API. Access is strictly read-only, with search, pagination, and recent-activity changelog support.

Controls the user's LinkedIn account through a logged-in browser session, enabling post publishing, profile viewing and editing, job searching, and Easy Apply submissions from chat.

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.

Dynamic tools to automate tasks on LinkedIn website.

MCP server for LinkedIn that enables AI agents to post, comment, like, and manage content on LinkedIn.

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

Enables an AI agent to fully operate a LinkedIn account—posting, messaging, profile edits, and network management—with self-healing selectors, human-like pacing, and approval-based planning to avoid breakage or lockouts.

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

Enables an AI agent to drive a real LinkedIn account through a persistent browser session, covering full profile editing, people and content interactions (searching, connecting, messaging, posting, reacting), and job search with step-by-step Easy Apply submissions. It reads data through LinkedIn's internal Voyager API while writing through the actual UI, with a saved answer bank so repeated application questions are resolved automatically.

A template for deploying an MCP server on Vercel, with example tools like roll_dice and get_weather.

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

Enables AI assistants to search LinkedIn job, internship and work-study listings and to turn Job IDs or LinkedIn URLs into complete offer details such as title, company, location, contract type, applicant count, direct apply link and full description, all without a LinkedIn account or API key.

Enables LLMs to manage LinkedIn posts and view analytics through a set of MCP tools, including creating, reading, and deleting posts, checking authentication, and retrieving profile info.

Enables signed-in users to create, edit, and delete their own LinkedIn posts, including text, images, video, documents, or article links, and to list locally tracked posts and check the authenticated account.

Enables running a stateless Model Context Protocol server over Streamable HTTP on Cloudflare Workers or any fetch-capable runtime, with signed sessions, origin checks, and JSON-RPC request handling. It lets developers define tools with JSON Schema validation and per-request context.