"How to find people on LinkedIn by name" matching MCP servers:

Local-first memory for AI agents about the people in your life. MCP server + CLI on SQLite. Never phones home.

Open MCP server for AI agents to discover people, jobs, collaborators and projects through semantic search over human-published context.

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

Enables governed interaction with synthetic people data through MCP tools, providing per-caller scoped access, semantic-layer metrics, and read-only SQL with authorization checks.

Enables MCP clients to search locally indexed text files, PDFs, and images using natural-language descriptions, and to index folders and inspect index statistics.

Enables an AI assistant to store, search, update, and reason over local, evidence-backed relationship memories so it can recall people's needs and offerings and suggest relevant connections.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

Enables AI agents to format, validate, and compare Japanese bank-transfer account names for Zengin compatibility, including half-width katakana conversion, legal-entity abbreviation rules, length checks, and reconciliation matching. All tools are read-only and offline.

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.

A discovery tool for AI agents to search, evaluate, and install MCP servers from multiple registries.

MCP server for querying a database of 1 million Korean personas with full-text search, enabling AI agents to retrieve detailed demographic, professional, and personal profiles.

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.

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

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 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 searching and scraping of LinkedIn for structured data on people, companies, and job listings. It allows AI clients to retrieve detailed profiles, experience, and activity sections using browser automation.

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 use an existing browser session to read profiles and companies, search jobs and people, and manage messages and connection requests on LinkedIn.

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

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 AI assistants to connect to LinkedIn, accessing profiles and companies, searching for jobs and people, managing saved jobs, updating job-search profile settings, and inspecting analytics.

MCP server that lets you analyze your own LinkedIn profile with a local LLM (LM Studio). It uses Playwright to reuse your browser session, fetch profile data as JSON, and provides tools for session management and profile analysis.

An MCP server that enables users to interact with LinkedIn feeds and search for job listings through natural language. It provides tools for retrieving recent feed posts and searching for professional opportunities based on specific keywords and locations.

Enables AI assistants to read and edit the user's own LinkedIn profile by driving a real logged-in Chrome session through CDP, with every write requiring explicit confirmation.

Enables MCP clients to read and write LinkedIn content through the Voyager API and to use an already logged-in Chrome session for messaging, posting, and referral workflows, with confirmation required before sends or publishes.

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.