LinkedIn MCP Pro Max

curl -LsSf https://astral.sh/uv/install.sh | sh

chmod +x scripts/setup.sh
./scripts/setup.sh

uv sync
uv run python -m patchright install chromium
cp .env.example .env

LINKEDIN_EMAIL="your-email@example.com"
LINKEDIN_PASSWORD="your-secure-password"
LINKEDIN_USERNAME="your-profile-slug"

uv run linkedin-mcp-pro-max --login

{
    "mcpServers": {
        "linkedin-mcp-pro-max": {
            "command": "/home/naimul/.local/bin/uv",
            "args": [
                "--directory",
                "/home/naimul/linkedin-mcp-pro-max",
                "run",
                "linkedin-mcp-pro-max"
            ]
        }
    }
}

[tools/]  →  [services/]  →  [browser/actors/ + browser/scrapers/]
              ctx.my_svc        manager.my_actor / manager.my_scraper

src/
├── app.py                  # Composition root — auto-wires from registry
├── helpers/
│   └── registry.py         # Unified discovery engine (ServiceMeta, ActorMeta, ScraperMeta)
├── tools/                  # MCP tool definitions (@mcp.tool) — auto-discovered
├── services/               # Business logic layer — auto-wired via SERVICE markers
├── browser/
│   ├── actors/             # Write operations (UI interaction) — auto-registered
│   ├── scrapers/           # Read operations (data extraction) — auto-registered
│   ├── manager.py          # Orchestrator — auto-instantiates actors/scrapers
│   └── helpers/            # Low-level browser utilities (driver, sniffer, dom)
├── api/                    # LinkedIn internal API client
├── db/                     # Database repositories
├── schema/                 # Pydantic domain models
├── config/                 # Settings and environment
└── providers/              # AI provider wrappers (OpenAI, Claude)

discover_all()
├── services/*.py     → SERVICE = ServiceMeta(...)   → injected into AppContext
├── browser/actors/*  → ACTOR   = ActorMeta(...)     → instantiated in BrowserManager
└── browser/scrapers/ → SCRAPER = ScraperMeta(...)   → instantiated in BrowserManager

from helpers.registry import ScraperMeta

class MyFeatureScraper:
    def __init__(self, page): ...
    async def scrape(self): ...

SCRAPER = ScraperMeta(attr="my_feature_scraper", cls=MyFeatureScraper)

from helpers.registry import ServiceMeta

class MyFeatureService:
    def __init__(self, browser=None): ...
    async def do_work(self): ...

SERVICE = ServiceMeta(attr="my_feature", cls=MyFeatureService, deps=["browser"], lazy=True)

from app import mcp, get_ctx

@mcp.tool()
async def my_feature_tool(param: str) -> str:
    """Description the AI reads to decide when to use this tool."""
    ctx = await get_ctx()
    await ctx.initialize_browser()
    result = await ctx.my_feature.do_work()
    return json.dumps(result)

uv run linkedin-mcp-pro-max             # Start MCP server
uv run linkedin-mcp-pro-max --login     # Autonomous headless login
uv run linkedin-mcp-pro-max --status    # Check authentication status
uv run linkedin-mcp-pro-max --logout    # Clear session and cookies