LinkedIn MCP server for Claude, Cursor and any AI agent

linkfetch-mcp gives any AI agent a full set of LinkedIn tools: search every public LinkedIn job since April 2026, look up companies, score and sort them with AI functions, and, through a LinkedIn account you connect, search people and posts, read profiles and your inbox, and send messages and connection requests.

It is a small stdio bridge to LinkFetch's hosted MCP server: every tool call goes to https://linkfetch.io/mcp with your API key, so the tools and prices are always current and nothing runs a browser on your machine. If your client supports remote MCP over HTTP, you can skip this package and use the URL directly.

Full tool list with prices, and setup for each client: linkfetch.io/mcp/claude

Tools

• Jobs and companies (no LinkedIn account needed): search_jobs, get_job, search_companies, get_company
• AI functions: ai_score, ai_classify, ai_extract, ai_write, each over up to 25 jobs or companies
• Your leads: list_leads, save_lead, list_lead_lists
• Through your connected LinkedIn account: people and company search, profiles, employees, posts and reactions, connections, invitations, conversations, messages, comments, reactions, follows

Each call costs a flat number of credits, stated in the tool's description. Every connected account works inside daily and weekly limits that LinkFetch enforces whatever the agent asks for.

Setup

Create an API key (lf_…) on the MCP page of your LinkFetch dashboard. New accounts start with free credits. Then add the server to your client: every client runs npx -y linkfetch-mcp with LINKFETCH_API_KEY set. Node.js 18+ is required.

Upgrading from 0.1.x? Keys starting with sk_live_ stopped working when LinkFetch 2 launched in October 2026. Create a new lf_… key and replace it in your config.

Claude Desktop

Settings → Developer → Edit Config, or edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) / %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "linkfetch": {
      "command": "npx",
      "args": ["-y", "linkfetch-mcp"],
      "env": { "LINKFETCH_API_KEY": "lf_..." }
    }
  }
}

Fully quit and reopen Claude.

Claude Code

claude mcp add linkfetch -e LINKFETCH_API_KEY=lf_... -- npx -y linkfetch-mcp

Cursor, Windsurf, Gemini CLI, Cline

These use the same mcpServers block as Claude Desktop above. Put it in:

Client	Config file
Cursor	~/.cursor/mcp.json (global) or .cursor/mcp.json (project)
Windsurf	~/.codeium/windsurf/mcp_config.json
Gemini CLI	~/.gemini/settings.json
Cline	MCP Servers → Configure → cline_mcp_settings.json

VS Code (GitHub Copilot agent mode)

.vscode/mcp.json:

{
  "servers": {
    "linkfetch": {
      "command": "npx",
      "args": ["-y", "linkfetch-mcp"],
      "env": { "LINKFETCH_API_KEY": "lf_..." }
    }
  }
}

OpenAI Codex CLI

~/.codex/config.toml:

[mcp_servers.linkfetch]
command = "npx"
args = ["-y", "linkfetch-mcp"]
env = { LINKFETCH_API_KEY = "lf_..." }

Zed

settings.json:

{
  "context_servers": {
    "linkfetch": {
      "command": "npx",
      "args": ["-y", "linkfetch-mcp"],
      "env": { "LINKFETCH_API_KEY": "lf_..." }
    }
  }
}

Your own agent

Any MCP client library can spawn the server over stdio. OpenAI Agents SDK (Python):

from agents import Agent, Runner
from agents.mcp import MCPServerStdio

async with MCPServerStdio(params={
    "command": "npx",
    "args": ["-y", "linkfetch-mcp"],
    "env": {"LINKFETCH_API_KEY": "lf_..."},
}) as linkfetch:
    agent = Agent(name="LinkedIn researcher", mcp_servers=[linkfetch])
    result = await Runner.run(agent, "Which companies in Berlin started hiring data engineers this week?")

LangChain users can load the same server with langchain-mcp-adapters.

No install: remote MCP

Clients that support remote MCP over Streamable HTTP can connect to the hosted server directly:

• URL: https://linkfetch.io/mcp
• Header: Authorization: Bearer lf_...

Claude (desktop or claude.ai): Settings → Connectors → Add custom connector, with https://linkfetch.io/mcp?key=lf_... as the URL.

Claude Code: claude mcp add --transport http linkfetch https://linkfetch.io/mcp --header "Authorization: Bearer lf_..."

Environment variables

Variable	Required	Default
LINKFETCH_API_KEY	yes		Your lf_… key
LINKFETCH_MCP_URL	no	https://linkfetch.io/mcp	Point at another LinkFetch MCP endpoint

Errors

A missing, old or rejected key comes back as an error on every request, with what to do about it, so the agent can tell you. Tool errors (no credits left, no LinkedIn account connected, a limit reached) come from the hosted server as normal tool results.

Development

npm install
npm run build
LINKFETCH_API_KEY=lf_... node dist/index.js

src/index.ts is the whole server: it opens one MCP client connection to the hosted server and forwards tools/list and tools/call to it.

License

MIT