LinkFetch: LinkedIn MCP

io.linkfetchv2.0.1Updated Oct 9, 2026

LinkedIn jobs, companies and people for AI agents, plus messages and invites via your own account.

Overview

AI-generated overview

Gives an AI assistant LinkedIn job, company and people search plus messaging and invites through a connected LinkedIn account.

What it does
LinkFetch exposes LinkedIn tools to an agent: searching public jobs and companies, retrieving job and company details, and running AI functions such as scoring, classifying, extracting and writing over up to 25 jobs or companies. It also manages saved leads and lead lists. Through a LinkedIn account you connect, it adds people and company search, profiles, employees, posts and reactions, connections, invitations, conversations, messages, comments, reactions and follows.
When to use it
Use it for recruiting, sales prospecting or market research where an assistant should search LinkedIn jobs, companies and people, score or sort results, and act on a connected LinkedIn account by sending messages or connection requests.
Requirements
Either a remote MCP endpoint over Streamable HTTP with an Authorization Bearer header, or the npm package linkfetch-mcp run locally over stdio with Node.js 18+ and the LINKFETCH_API_KEY environment variable. A LinkFetch API key created on the dashboard is required; new accounts start with free credits. A connected LinkedIn account is needed for people, posts, inbox and messaging tools.
Before you install
Every tool call costs credits, and connected accounts are subject to daily and weekly limits enforced by the service. Tools can send messages, connection requests, comments, reactions and follows from your LinkedIn account, and can save leads. The API key (LINKFETCH_API_KEY or the Authorization header) is a secret; older sk_live_ keys no longer work. Tool calls and your key are sent to the hosted LinkFetch server.

Installation

In SourceWeft

  1. Open LinkFetch: LinkedIn MCP in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "linkedin": {
      "type": "http",
      "url": "https://linkfetch.io/mcp"
    }
  }
}

README

LinkedIn MCP server for Claude, Cursor and any AI agent

[npm] [License: MIT] [MCP Registry]

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):

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

Fully quit and reopen Claude.

Claude Code

bash
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:

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

VS Code (GitHub Copilot agent mode)

.vscode/mcp.json:

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

OpenAI Codex CLI

~/.codex/config.toml:

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

Zed

settings.json:

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):

python
from agents import Agent, Runnerfrom 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

VariableRequiredDefault
LINKFETCH_API_KEYyesYour lf_… key
LINKFETCH_MCP_URLnohttps://linkfetch.io/mcpPoint 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

bash
npm installnpm run buildLINKFETCH_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

Source: README.md at commit fd05ba1

Tools

0
Tool metadata has not been indexed yet.

Version history

1
  1. v2.0.1LatestOct 9, 2026