Server data from the Official MCP Registry
LinkedIn jobs, companies and people for AI agents, plus messages and invites via your own account.
About
LinkedIn jobs, companies and people for AI agents, plus messages and invites via your own account.
Remote endpoints: streamable-http: https://linkfetch.io/mcp
Security Report
Valid MCP server (2 strong, 4 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry.
Endpoint verified · Requires authentication · 2 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
Environment variable: LINKFETCH_API_KEY
How to Install & Connect
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
Documentation
View on GitHubFrom the project's GitHub README.
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 newlf_…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
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