LinkedIn Buddy

LinkedIn Buddy

MCP server for LinkedIn automation that enables AI agents to perform LinkedIn actions (search, inbox, feed, jobs, etc.) safely with human-like evasion and two-phase commit preview.

Category
Visit Server

README

<p align="center"> <img src="./assets/brand/banner.png" alt="LinkedIn Buddy — the chameleon that blends in" width="720" /> </p>

<p align="center"> <strong>LinkedIn automation that doesn't get you banned.</strong><br> <em>CLI · MCP Server · TypeScript API — one runtime, three surfaces.</em> </p>

<p align="center"> <a href="https://github.com/sigvardt/linkedin-buddy/actions/workflows/ci.yml"><img src="https://img.shields.io/github/actions/workflow/status/sigvardt/linkedin-buddy/ci.yml?branch=main&label=CI" alt="CI status" /></a> <a href="https://www.npmjs.com/"><img src="https://img.shields.io/badge/npm-publish--ready-CB3837?logo=npm&logoColor=white" alt="npm publish ready" /></a> <a href="https://github.com/sigvardt/linkedin-buddy/stargazers"><img src="https://img.shields.io/github/stars/sigvardt/linkedin-buddy?style=flat" alt="GitHub stars" /></a> <a href="https://modelcontextprotocol.io/"><img src="https://img.shields.io/badge/MCP-compatible-1f6feb" alt="MCP compatible" /></a> <a href="https://nodejs.org/"><img src="https://img.shields.io/badge/Node-22%2B-339933?logo=node.js&logoColor=white" alt="Node.js 22+" /></a> <a href="https://www.typescriptlang.org/"><img src="https://img.shields.io/badge/TypeScript-strict-3178c6?logo=typescript&logoColor=white" alt="TypeScript strict" /></a> <a href="#license"><img src="https://img.shields.io/badge/License-pending-lightgrey" alt="License pending" /></a> </p>

<p align="center"> <a href="#get-running-in-60-seconds">Install</a> · <a href="#plug-into-your-ai">MCP Setup</a> · <a href="#go-deeper">Features</a> · <a href="#use-the-typescript-api">TypeScript API</a> · <a href="#docs">Docs</a> </p>


You've been doing LinkedIn wrong.

Scraping with Python scripts that break every Tuesday. Rate-limited by APIs that don't actually exist. Copy-pasting from the web UI like it's 2015. Running Chrome extensions that sell your session cookies to whoever's buying.

Stop.

LinkedIn Buddy is a local-first Playwright runtime that operates LinkedIn the way you would — just faster, safer, and without the RSI. Anti-bot evasion, persistent browser profiles, and a two-phase commit system that previews every single write before it fires. Nothing touches LinkedIn until you say so.

<!-- chameleon at laptop pose -->

  • Three surfaces. One runtime. CLI for operators, MCP server for AI agents, TypeScript API for builders. Same services, same safety guarantees, zero duplication.
  • Every write previews first. Two-phase commit. Prepare, inspect, confirm. No accidental DMs. No "oops, wrong connection request."
  • The chameleon blends in. Human-like typing, Poisson-distributed pauses, Bézier mouse paths. LinkedIn sees a person, not a bot.
  • Your machine. Your data. SQLite state, persistent profiles, structured logs, screenshots. Nothing leaves your laptop. No cloud. No telemetry. No accounts.
  • 100+ MCP tools. Claude Desktop, Cursor, Cline — your agent gets full LinkedIn access through structured tool calls, not brittle prompt hacks.

<p align="center"> <img src="./assets/media/demo/core-workflow.gif" alt="Terminal demo: install, authenticate, search LinkedIn" width="720" /> </p>


Get running in 60 seconds.

You're a developer. You've done this before.

git clone https://github.com/sigvardt/linkedin-buddy.git
cd linkedin-buddy
npm install
npx playwright install chromium
npm run build

Authenticate and verify:

npm exec -w @linkedin-buddy/cli -- linkedin login --profile default
npm exec -w @linkedin-buddy/cli -- linkedin status --profile default

Run your first search:

npm exec -w @linkedin-buddy/cli -- linkedin search "developer relations" --category people --limit 5

That's it. You're in.

Tip: The CLI installs three equivalent binaries — linkedin, lbud, and linkedin-buddy. After a global install (once published), drop the npm exec prefix entirely:

lbud search "developer relations" --category people --limit 5

Prefer manual encrypted session capture over browser-based login?

npm exec -w @linkedin-buddy/cli -- linkedin auth session --session default

Install and build terminal


Plug into your AI.

Paste this into your MCP client config. Done.

{
  "mcpServers": {
    "linkedin": {
      "command": "npm",
      "args": ["exec", "-w", "@linkedin-buddy/mcp", "--", "linkedin-mcp"]
    }
  }
}

Works with Claude Desktop, Cursor, Cline, and every MCP-compatible client. 100+ tools. Zero boilerplate. Your AI agent interacts with LinkedIn through structured tool calls — not screen-scraping, not prompt engineering, not prayer.

Tools to start with: linkedin.session.status · linkedin.search · linkedin.inbox.list_threads · linkedin.feed.list · linkedin.jobs.search · linkedin.notifications.list · linkedin.actions.confirm · linkedin.activity_poller.run_once

MCP quick connect terminal

MCP client integration diagram


Go deeper.

🔍 Search everything.

<!-- chameleon with phone pose -->

People, companies, posts, jobs, groups, events. One unified surface, structured results.

npm exec -w @linkedin-buddy/cli -- linkedin search "staff engineer" --category people --limit 5
npm exec -w @linkedin-buddy/cli -- linkedin search "open source ai" --category posts --limit 5
npm exec -w @linkedin-buddy/cli -- linkedin jobs search "product manager" --location Copenhagen --limit 10

Search surface illustration


💬 Inbox. Read it. Reply safely.

<!-- chameleon at laptop pose -->

List threads, read messages, stage replies. Every outbound message goes through two-phase commit — you see exactly what will send before it sends.

npm exec -w @linkedin-buddy/cli -- linkedin inbox list --limit 10
npm exec -w @linkedin-buddy/cli -- linkedin inbox show --thread <thread-url-or-id> --limit 20
npm exec -w @linkedin-buddy/cli -- linkedin inbox prepare-reply --thread <thread-url-or-id> --text "Thanks for reaching out."
npm exec -w @linkedin-buddy/cli -- linkedin actions confirm --token ct_...

📝 Feed and posts. Comment without regret.

<!-- chameleon writing pose -->

Browse the feed, view posts, stage comments. The confirm flow means you see exactly what will post before it posts. Create text posts, media posts, and polls through the same two-phase pipeline.

npm exec -w @linkedin-buddy/cli -- linkedin feed list --limit 5
npm exec -w @linkedin-buddy/cli -- linkedin feed view <post-url>
npm exec -w @linkedin-buddy/cli -- linkedin feed comment <post-url> --text "Insightful breakdown. Thanks for sharing."
npm exec -w @linkedin-buddy/cli -- linkedin actions confirm --token ct_...

Confirmed actions illustration


💼 Jobs. Search, save, apply.

<!-- chameleon with briefcase pose -->

Full job search with location filters and Easy Apply support. Save jobs, manage alerts, track everything locally in SQLite.

npm exec -w @linkedin-buddy/cli -- linkedin jobs search "product manager" --location Copenhagen --limit 10

👤 Profiles, companies, and notifications.

Inspect any profile, browse company pages, manage your notification feed.

npm exec -w @linkedin-buddy/cli -- linkedin profile view me
npm exec -w @linkedin-buddy/cli -- linkedin company view openai
npm exec -w @linkedin-buddy/cli -- linkedin notifications list --limit 20

☕ Activity polling. Webhooks that actually work.

<!-- chameleon with coffee pose -->

Set up watches on LinkedIn activity. Get notified when things change. Fan out webhooks with HMAC-signed payloads and automatic retry logic.

npm exec -w @linkedin-buddy/cli -- linkedin activity watch add --profile default --kind notifications --interval-seconds 600
npm exec -w @linkedin-buddy/cli -- linkedin activity webhook add --watch <watch-id> --url https://example.com/hooks/linkedin
npm exec -w @linkedin-buddy/cli -- linkedin activity run-once --profile default

Activity webhooks illustration


Every write previews before it executes. No accidents.

<!-- chameleon thumbs up pose -->

This isn't a YOLO automation tool. Every outbound action — messages, connection requests, comments, profile edits, posts — goes through two-phase commit:

  1. Prepare → Action stored in SQLite, preview returned, confirm token generated.
  2. Review → You (or your AI agent) inspect exactly what will happen.
  3. Confirm → Token validated, action executed, result recorded.

Tokens expire in 30 minutes. HMAC-SHA256 sealed with entropy. No confirmation, no execution. Period.

Confirm before write terminal


The chameleon blends in.

LinkedIn's bot detection is aggressive. LinkedIn Buddy doesn't fight it — it disappears.

  • Human-like typing with configurable typo rates and correction pauses
  • Poisson-distributed delays between actions — not fixed sleeps, real statistical distributions
  • Bézier curve mouse paths — smooth, natural movement with overshoot and correction
  • Fingerprint hardening — WebGL, canvas, timezone, locale, all consistent per profile
  • Four evasion levelsoff · light · moderate (default) · aggressive

Configure via --evasion-level, LINKEDIN_BUDDY_EVASION_LEVEL env var, or runtime options. See docs/evasion.md for the full breakdown.


Use the TypeScript API.

Skip the CLI. Embed the full runtime in your own apps.

import { createCoreRuntime } from "@linkedin-buddy/core";

const runtime = createCoreRuntime();

try {
  const result = await runtime.search.search({
    profileName: "default",
    category: "people",
    query: "developer relations",
    limit: 5,
  });

  console.log(result.results.map((person) => person.name));
} finally {
  runtime.close();
}

Same services, same two-phase commit safety, same evasion layer. Everything the CLI and MCP server use, exposed as clean TypeScript APIs with full type definitions.


Architecture.

Local-first. No cloud. No third-party servers. Everything runs on your machine.

Architecture Workflow
System architecture diagram Workflow: install to daily use

The runtime wires 25+ services through constructor injection. No circular dependencies.

Infrastructure:  DB → Logger → Artifacts → ProfileManager → Auth → RateLimiter → TwoPhaseCommit
                                                                        ↓
LinkedIn:        Inbox, Feed, Connections, Profile, Search, Jobs, Notifications,
                 Posts, Publishing, Followups, Groups, Events, CompanyPages,
                 Members, PrivacySettings, Analytics
                                                                        ↓
Activity:        Watches → Poller → Webhooks → Scheduler

How it compares.

Tool CLI MCP Dev API Confirm-before-write Best fit
LinkedIn Buddy Local-first workflows for operators and AI agents
stickerdaniel/linkedin-mcp-server MCP-focused LinkedIn scraping and job search
tigillo/linkedin-cli Terminal-oriented LinkedIn usage
alabarga/linkedin-api Library-style LinkedIn integrations

See docs/repository-seo.md for keyword targets and the GitHub-search baseline.


Terminal snapshots.

Install and build MCP quick connect Confirm before write
Install and build MCP setup Confirm flow

Docs.

Need Doc
Activity polling and webhooks docs/activity-webhooks.md
Anti-bot evasion profiles docs/evasion.md
E2E and replay testing docs/e2e-testing.md
Live validation and account safety docs/write-validation.md
Selector auditing docs/selector-audit.md
Draft quality evaluation docs/draft-quality-evaluation.md
Brand and social preview assets docs/brand-guidelines.md
README media research docs/readme-media-research.md
Media asset inventory assets/media/README.md
Articles and newsletters docs/articles-newsletters.md
Notifications docs/notifications.md
Rate limiting docs/rate-limiting.md
Jobs, alerts, and Easy Apply docs/jobs.md
SEO targets and metadata docs/repository-seo.md

Contributing.

Start with CONTRIBUTING.md. Be decent (CODE_OF_CONDUCT.md). Report security issues through SECURITY.md.

If you change CLI commands, MCP tools, or write flows — update the README and the relevant docs so new users discover the feature.


Star history.

Star History Chart


Author's note.

LinkedIn's API is locked behind partner programs most developers will never access. The web UI is designed for humans clicking buttons one at a time. Every existing tool is either a fragile Python scraper, a Chrome extension with questionable permissions, or a wrapper around endpoints that don't actually exist publicly.

I built LinkedIn Buddy because I needed LinkedIn automation that worked. Not a demo. Not a proof-of-concept that impresses on Twitter and breaks in production. A real tool that handles authentication, evades detection, previews every action before executing, and runs entirely on my own machine.

The two-phase commit system isn't a nice-to-have — it's the thing that lets AI agents use LinkedIn without accidentally messaging your CEO. The evasion layer isn't paranoia — it's the difference between a tool that works for a week and one that works for months.

100% open source. No telemetry. No cloud. No accounts. Your data stays on your machine.

Find it useful? Star the repo. Find a bug? Open an issue. Have a better approach? PRs are welcome.


License

License: pending repository selection.

Built with Playwright, Commander, better-sqlite3, and the Model Context Protocol SDK.

Release notes in CHANGELOG.md.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured