Linkedin Mcp

🔗 LinkedIn MCP

LinkedIn for AI assistants — structured data via a real, stealth browser session

[](https://github.com/devag7/linkedin-mcp/actions/workflows/ci.yml) [](https://www.npmjs.com/package/linkedin-mcp-tools) [](LICENSE) [](https://www.typescriptlang.org/) [](https://modelcontextprotocol.io/) [](https://glama.ai/mcp/servers/devag7/linkedin-mcp)

Give Claude, Cursor, and any MCP client access to LinkedIn — profiles, people/job/company search, feed, messaging, and your network — as clean structured JSON.

22 tools · reads + gated writes (connect, message, post, react, comment) · a real safety layer (daily caps, human pacing, circuit breaker) · 166 tests.

> ⚠️ Automating LinkedIn violates its User Agreement and can get an account restricted. No tool is ban-proof — and this one says so up front. Use a secondary account; read [Account safety](#-account-safety) and [DISCLAIMER.md](DISCLAIMER.md) first.

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Why this exists

LinkedIn's internal Voyager API (the one its own web app uses) returns rich, structured JSON — but it sits behind Cloudflare bot-management, which rejects plain HTTP requests (a stateless fetch or curl gets stuck in an endless redirect, even with a valid cookie). The only reliable way to read LinkedIn data programmatically in 2026 is from inside a real browser that clears the challenge.

This project's approach:

1. Drive a real Chrome via patchright (an undetected Playwright fork) so Cloudflare's challenge is solved with a genuine browser fingerprint.
2. Query Voyager from inside the authenticated page — same-origin, the exact network path LinkedIn's own SPA uses → structured JSON, not scraped DOM text.

That last point is the edge over DOM-scraping tools: in-page API calls are locale-independent and resilient to UI redesigns, so they don't break on a moved CSS selector or a translated label.

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✨ What's good here

| | | |---|---| | 🧩 Structured JSON | In-page Voyager API calls return normalized data, shaped into compact objects — not brittle innerText scraping. | | ✍️ Writes are API calls, not button-clicking | connect / message / post / react / comment POST straight to Voyager — the exact requests the web app sends, captured and verified live. No hunting for a "Connect" button under a sticky navbar, no composer-dialog race. Every write returns a structured status (ok / duplicate / already_connected / restricted / quota_exhausted / …) — never a blind "sent: true". | | 🛡️ Safety layer built in | Serial queue, human-paced jittered delays, per-action daily budgets, account warmup ramp, and a circuit breaker that hard-stops on any checkpoint/captcha. (Risk reduction — not a safety guarantee.) | | 🔥 One warm session | A single persistent browser per process (cookies + Cloudflare clearance survive restarts). Explicit close_session, signal-handled teardown — no zombie Chrome. | | 🌍 Locale-independent | API + embedded-JSON parsing, not English-only DOM selectors — survives UI redesigns and translations. | | 🔒 Local & private | Session stored under ~/.linkedin-mcp/ with 0700/0600 perms; no cookies/tokens to paste, none ever logged. |

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How it compares

| | DOM-scraping LinkedIn MCPs | This | |---|---|---| | Reads | scraped page text (brittle, locale-bound) | structured API JSON | | Writes (connect/message/post) | click rendered buttons (break on sticky navbars, dialog races, localized labels) | direct Voyager POST, captured + verified live | | Write feedback | "clicked it" → hope | structured status (ok / duplicate / restricted / quota_exhausted / …) | | Resilience | breaks on UI tweaks / translations | API + embedded-JSON, locale-proof | | Safety (caps, pacing, circuit breaker) | none | ✅ built-in, 166 tests | | Zombie browser processes | common | ✅ reaped on close | | Language | Python | TypeScript + official MCP SDK |

We hit LinkedIn's own API from inside the challenge-passed browser — reads and writes — so you get the structured response and a real status, not parsed HTML and a hopeful click.

📦 Status

Stable — v2, all 22 tools shipping. Full transparency on exactly where every piece stands:

| Area | State | |---|---| | Stealth browser engine (patchright) | ✅ built, live-proven | | In-page Voyager fetch (the core mechanism) | ✅ live-verified (returns structured JSON) | | Safety layer (queue / pacer / budgets / circuit-breaker) | ✅ built, 166 unit tests | | Profile — get_profile, get_my_profile (name, headline, summary, experience, education, skills, certifications, languages) | ✅ live-verified | | Feed / notifications — get_feed, get_notifications | ✅ live-verified | | Jobs / messaging — search_jobs, get_job_details, get_inbox, get_conversation | ✅ live-verified | | People / companies — search_people, search_companies, get_company, get_company_posts, get_company_employees (DOM fallback) | ✅ live-verified | | Network — get_pending_invitations (received + sent) | ✅ | | Session — whoami, health_check (live Voyager probe + budget headroom), close_session | ✅ | | Write tools — connect_with_person, send_message, create_post, react_to_post, comment_on_post | ✅ all 5 endpoints captured + live-verified on a burner; gated (confirm:true + daily caps), structured statuses. ⚠️ These take real, often irreversible actions — keep the gate on and use a throwaway account. |

22 tools. typecheck + 166 tests green.

Login is headful, the server is headless. The one-time --login opens a real Chrome window (to clear Cloudflare and let you solve any captcha/2FA). After that the persistent profile carries the clearance, so the server runs headless — verified returning live data. Use a residential IP; datacenter/VPN IPs are often pre-flagged by Cloudflare regardless of headless vs headful.

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🚀 Quick start

1. Log in once (opens a real Chrome window — sign in, solve any captcha/2FA):

npx -y linkedin-mcp-tools@latest --login

Needs Google Chrome installed (or run npx patchright install chrome once). Your session — Cloudflare clearance and all — persists to ~/.linkedin-mcp/profile/.

2. Point your MCP client at it. Claude Desktop / Cursor / Claude Code config:

{
  "mcpServers": {
    "linkedin": {
      "command": "npx",
      "args": ["-y", "linkedin-mcp-tools@latest"]
    }
  }
}

Then just ask: "Get my LinkedIn profile and summarize my experience" or "Find 5 recruiters at Google."

From source / contributing

git clone https://github.com/devag7/linkedin-mcp.git
cd linkedin-mcp
npm install
npm run setup:browser     # installs the Chrome patchright drives
npm run login             # log in once
npm run spike             # verify: fetches your profile as JSON
npm run build             # produces dist/

MCP config: "command": "node", "args": ["/absolute/path/to/dist/index.js"].

Headless / server deployment

The one-time --login needs a window; the server then runs headless (verified returning live data). Run --login on a machine with a display (or via VNC), copy ~/.linkedin-mcp/profile/ to your server, and run there:

LINKEDIN_HEADLESS=true npx -y linkedin-mcp-tools@latest   # no display needed

Use a residential IP — datacenter/VPN IPs are frequently pre-flagged by Cloudflare regardless of headless vs headful.

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🛡️ Account safety

Read this. Automating LinkedIn violates its User Agreement and can get your account restricted or banned — no tool can prevent that, including this one. The built-in safety features (daily caps, human pacing, warmup, circuit breaker) reduce risk; they do not eliminate it.

Defaults err conservative:

• Connections 20/day, messages 50/day, likes+comments 50/day combined, follows 30/day — combined write cap 150/24h.
• Profile views 80/day, searches 30/day.
• New-account warmup ramp over the first weeks; pending-invite ceiling and acceptance-rate pauses.
• Reads paced 4–12s apart, writes 45–150s, with long breaks and a working-hours gate.
• A circuit breaker stops automatically on any checkpoint, captcha, or "unusual activity" page — and never tries to solve one.

Recommendations: use a secondary/throwaway account, run from a residential IP, warm it up slowly. See [DISCLAIMER.md](DISCLAIMER.md) for the full legal/ToS notice.

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⚙️ Configuration

| Variable | Default | Description | |---|---|---| | LINKEDIN_HEADLESS | true | Server runs headless. --login always opens a real window regardless. Set false to watch the browser. | | LINKEDIN_CHROME_PATH | — | Explicit Chrome binary path (else patchright's). | | LINKEDIN_PROFILE_DIR | ~/.linkedin-mcp/profile | Persistent browser profile. | | LINKEDIN_IDLE_TIMEOUT_MS | 300000 | Close the browser after this idle time (0 disables). | | LINKEDIN_CONCURRENCY | 1 | Serial by default; >1 is ban-risky. | | TRANSPORT | stdio | stdio (primary) or http. |

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🛠 Development

npm run dev          # run from source (stdio)
npm run typecheck
npm test             # vitest (safety layer + smoke)
npm run build

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📄 License

MIT — see [LICENSE](LICENSE). Not affiliated with LinkedIn. Use at your own risk; see [DISCLAIMER.md](DISCLAIMER.md).

[](https://glama.ai/mcp/servers/devag7/linkedin-mcp)

Made by Dev Agarwalla

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: devag7
• Source: devag7/linkedin-mcp
• License: MIT
• Homepage: https://github.com/devag7/linkedin-mcp#readme

Install and usage instructions live in the source repository linked above.