MCP 服务器

GTM API LinkedIn MCP Server

A managed MCP server that gives AI agents 160+ typed LinkedIn tools for searching, connecting, messaging, and enriching profiles, with built-in account safety enforcement.

README

GTM API: LinkedIn MCP Server

GTM API is a managed LinkedIn MCP server. It gives an AI agent one key and 160+ typed LinkedIn tools over the Model Context Protocol, so Claude, ChatGPT or Cursor can search, connect, message and enrich on a LinkedIn account you own, with account safety enforced server side.

This repository holds the public interface: what the server exposes, how to connect a client, and how the safety layer works.

What is a LinkedIn MCP server?

A LinkedIn MCP server exposes LinkedIn actions as Model Context Protocol tools, so an AI agent calls them directly, the way a person would click through the UI. LinkedIn publishes no official API for invitations, member messages or open profile search, so a LinkedIn MCP server works through an account you own rather than through LinkedIn's developer platform.

Two shapes exist today. Cookie-driven open-source servers run a browser session with your own cookie and no pacing. Managed servers run each account in isolated infrastructure with limits enforced before every action. GTM API is the second kind.

Which clients it works with

Any MCP-compatible client:

Claude (Desktop, Code, and the API)
Cursor
ChatGPT (via connectors)
LangChain, n8n, and custom agent runtimes

Not using MCP? Every tool is also a typed REST endpoint with webhooks. One schema generates all three surfaces.

Quickstart

1. Get an API key. Sign up at app.gtm-api.com (7-day trial, no card) and connect a LinkedIn account. It opens in a dedicated anti-detect cloud browser with its own proxy.

2. Add the server to your MCP client. For Claude Desktop, edit claude_desktop_config.json (example in examples/):

{
  "mcpServers": {
    "gtm-api": {
      "url": "https://mcp.gtm-api.com/mcp",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

Prefer Docker? The same server as a command, through the gtmapi/linkedin-mcp launcher image (config in examples/):

{
  "mcpServers": {
    "gtm-api": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "-e", "GTM_API_KEY", "gtmapi/linkedin-mcp"],
      "env": { "GTM_API_KEY": "YOUR_API_KEY" }
    }
  }
}

3. Restart the client and prompt in plain English:

"Every morning, accept new connection invitations from founders, reply with a short welcome, and add anyone hiring SDRs to a warm list."

The agent discovers the tools and chains them: get_my_latest_linkedin_connection_invitations then accept_linkedin_connection_invitation then send_linkedin_message. Every outward action runs a preview-then-confirm step and a server-side daily-limit check before it reaches LinkedIn.

What the agent can do

160+ typed tools across 10 LinkedIn toolsets, grouped here into seven areas:

Toolset	Representative tools
Messaging	`send_linkedin_message`, `send_linkedin_voice_message`, `send_linkedin_inmail`, `send_linkedin_sales_nav_message`, inbox search and sync
Network	`send_linkedin_connection_request`, `accept_linkedin_connection_invitation`, withdraw and ignore, connections and followers
Content	track posts and metrics, comment, react, get engagers and commenters
Enrichment	lite and full profile, experience, skills, education, company data
Search	people, company and post search, similar profiles, employees, decision-makers, saved searches
Account health	smart limits, health snapshots, quota-hit, block and activity logs
Infrastructure	anti-detect cloud browsers, dedicated proxies, webhooks

LinkedIn is the live channel today. Email (Gmail, Outlook, IMAP), messengers (WhatsApp, Telegram, Instagram DMs) and calendars (Google, Microsoft) are on the roadmap on the same typed contract.

Is it safe for my LinkedIn account?

Safety is enforced by the server itself, under every tool call. Six mechanisms:

Owned accounts. The agent acts through an account you connected and control. There is no shared account pool.
Session isolation. Each account runs in its own anti-detect cloud browser with a dedicated proxy. One account, one session, one device signature.
Warm-up. A new account starts at a fraction of platform maximum, and its allowance is raised programmatically as the account ages and builds history.
Server-side limits. Per-action daily budgets are checked before dispatch, across 16 action buckets.
Randomized pacing. Bulk work is spread with per-gap randomized intervals, because a fixed cadence is itself a detectable pattern.
Preview then confirm. Outward actions return a preview and require confirmation, so an over-eager agent cannot burn an account.

On this setup GTM API reports 20,000+ LinkedIn accounts running at under 1% monthly ban. Full method: gtm-api.com/safe-linkedin-automation.

How it compares to open-source LinkedIn MCP servers

Cookie-driven servers such as stickerdaniel/linkedin-mcp-server run a browser session with your own LinkedIn cookie and leave pacing to you: the project's README documents the cookie login flow and lists no rate limiting. Apify's LinkedIn actors are a different shape, hosted scrapers priced per result and focused on pulling data out.

	GTM API (managed)	Cookie-driven open source
Account model	Owned, warmed, isolated	Your live cookie session
Safety layer	Anti-detect browser, dedicated proxy, limits	Not built in
Limit enforcement	Server side, before every action	You build it
Sends (connect, message, InMail)	Yes, with preview then confirm	Partial or none
Published ban rate	Self-reported: under 1% monthly across 20,000+ accounts	Not published
Support	Managed	Community
Price	From $19 per connected account per month	Free, run it yourself
Self-hosted, auditable code	No, managed service	Yes

Pricing

From $19 per connected account per month, scaling to $5 at volume, with unlimited API calls and no per-action fees. 7-day trial, no card. Enrichment and Signals are optional metered add-ons: gtm-api.com/pricing.

A note on LinkedIn's terms

LinkedIn's User Agreement does not permit third-party automation, so every tool in this space carries risk and no vendor can honestly promise otherwise. GTM API reduces that risk by acting only on accounts you own, with warm-up, human-like pacing and enforced limits, which is why the reported ban rate is under 1%. This is not legal advice.