LinkedIn Analyzer

Analyze your own LinkedIn profile through LM Studio using an MCP server and Playwright — without the official LinkedIn API.

The tool reuses your existing browser session (including 2FA) to fetch your profile data as structured JSON, which a local LLM can then analyze for optimization opportunities.

⚠️ Legal / Compliance notice

• This tool uses browser automation, not LinkedIn's official API.

• Using it may violate LinkedIn's Terms of Service. Account restrictions are theoretically possible.

• Use it only for your own profile, for personal, non-commercial purposes. Do not scrape third-party profiles, do not hammer the site.

• You are solely responsible for how you use this software.

Related MCP server: LinkedIn MCP Pro Max

Architecture

┌─────────────┐      ┌──────────────┐      ┌─────────────────────┐      ┌──────────┐
│ LM Studio   │ ───→ │ MCP Server   │ ───→ │ Background Server   │ ───→ │ Browser  │
│ (LLM)       │ MCP  │ (stdio)      │ HTTP │ (127.0.0.1:8766)    │      │ Playwright│
└─────────────┘      └──────────────┘      └─────────────────────┘      └──────────┘

Prerequisites

• Python 3.10+

• LM Studio (local)

• A LinkedIn account (you will log in manually once)

• Playwright browser: the project drives the browser via Playwright. Run playwright install chromium (step 4 below) once — it downloads a managed Chrome for Testing build automatically. No separate Chrome or Chrome for Testing installation is required.

Installation

# 1. Clone and enter the repo
git clone <your-repo-url>
cd linkedin-analyzer

# 2. Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate      # macOS/Linux
# or: venv\Scripts\activate    # Windows

# 3. Install dependencies
pip install -r requirements.txt

# 4. Install the Playwright browser
playwright install chromium

# 5. Configure
cp .env.example .env
# edit .env as needed (see below)

Configuration (.env)

Running

Option A — Start the daemon manually

./start-daemon.sh          # starts background_server.py on PORT (default 8766)
./stop-daemon.sh           # stops it again

The background server must keep running while you use the MCP tools — it holds the browser open.

Verify it is up:

curl http://127.0.0.1:8766/health

Option B — Auto-start wrapper (recommended for LM Studio)

Use scripts/linkedin-analyzer-mcp-wrapper.sh as the MCP command in LM Studio. It ensures a session key exists, starts the background server if needed, waits until it is healthy, then runs the MCP server:

{
  "mcpServers": {
    "linkedin-analyzer": {
      "command": "/path/to/linkedin-analyzer/scripts/linkedin-analyzer-mcp-wrapper.sh",
      "args": ["--stdio"]
    }
  }
}

Note: point the command at the full absolute path of the wrapper inside your clone (the wrapper derives all other paths from its own location). If LM Studio reports it cannot start the server, the path is almost always wrong — e.g. a command not found from a stale filename.

Setup in LM Studio

1. Add the MCP server (see above) and restart LM Studio.

2. Start a chat with the system prompt — pick docs/system-prompt.en.md (or the German docs/system-prompt.de.md) and paste it in.

3. Ask the assistant to check your session or analyze your profile.

First login (one-time)

1. Call the linkedin_login tool — the browser opens at LinkedIn's login page.

2. Log in manually in the browser (2FA is supported).

3. The session auto-saves as soon as the login is detected. You can also force it with linkedin_save_session.

4. Verify with linkedin_check_session.

MCP tools

HTTP API (background server)

Security

Important: The browser_sessions/ files contain login tokens. They are encrypted, but treat them like passwords. The key lives in SESSION_ENCRYPTION_KEY_FILE (default ~/.linkedin-analyzer/session.key). Both are git-ignored — never commit them.

Troubleshooting

"Not logged in" / authwall redirects

curl -X DELETE http://127.0.0.1:8766/session   # clear session
curl -X POST http://127.0.0.1:8766/login       # log in again in the opened browser

Browser does not open

• Make sure BROWSER_HEADLESS=False in .env (or unset).

• Reinstall the browser: playwright install chromium

• On Linux only, you may also need system libraries: playwright install-deps

Server not reachable

• Is it running? curl http://127.0.0.1:8766/health

• Port taken? Set another PORT in .env (the wrapper respects PORT too).

LinkedIn shows a captcha / rate limit

• Wait a few hours.

• Clear the session and log in again.

• Do not send requests too frequently.

Project layout

linkedin-analyzer/
├── background_server.py        # Long-running daemon (keeps browser open, HTTP API)
├── session_manager.py          # Encrypted session persistence
├── config.py                   # Environment configuration
├── mcp-server/
│   └── linkedin_mcp.py         # MCP server for LM Studio (stdio)
├── scripts/
│   └── linkedin-analyzer-mcp-wrapper.sh # Optional auto-start wrapper for LM Studio
├── docs/
│   ├── system-prompt.en.md     # English system prompt for LM Studio
│   └── system-prompt.de.md     # German system prompt for LM Studio
├── start-daemon.sh / stop-daemon.sh
├── requirements.txt
├── .env.example
└── browser_sessions/           # Encrypted sessions (git-ignored)

Development

Test the MCP server directly:

venv/bin/python mcp-server/linkedin_mcp.py --stdio

Then send JSON-RPC lines over stdin (initialize, tools/list, tools/call).

License

MIT — see LICENSE.

Credits

• Playwright — browser automation

• FastAPI — API framework

• MCP Protocol — LLM integration