linkedin-mcp-pro-max

<p align="center"> <h1 align="center">LinkedIn MCP Pro Max</h1> </p> <p align="center"> A high-performance, autonomous <strong>Model Context Protocol (MCP)</strong> server that turns LinkedIn into an API for your AI workflows. Built with <strong>Clean Architecture</strong>, stealth browser automation, and a convention-based zero-config component registry. </p> <p align="center"> <a href="#features"> <img src="https://img.shields.io/badge/Tools-14_Unified-blue?style=for-the-badge&logo=rocket" alt="Tools"> </a> <a href="https://github.com/astral-sh/uv"> <img src="https://img.shields.io/badge/Package_Manager-uv-purple?style=for-the-badge&logo=python" alt="UV"> </a> <a href="https://github.com/patchright/patchright"> <img src="https://img.shields.io/badge/Automation-Patchright-green?style=for-the-badge&logo=playwright" alt="Patchright"> </a> <a href="LICENSE"> <img src="https://img.shields.io/badge/License-MIT-yellow?style=for-the-badge" alt="License"> </a> </p> --- ## Quick Start ### 1. Prerequisites Ensure you have **[uv](https://docs.astral.sh/uv/)** installed: ```bash curl -LsSf https://astral.sh/uv/install.sh | sh ``` ### 2. Installation & Setup #### Method A: Automated Setup (Recommended) ```bash chmod +x scripts/setup.sh ./scripts/setup.sh ``` The script handles dependency syncing, `.env` bootstrapping, and stealth browser provisioning. #### Method B: Manual Setup ```bash uv sync uv run python -m patchright install chromium cp .env.example .env ``` Edit `.env` with your LinkedIn credentials: ```env LINKEDIN_EMAIL="your-email@example.com" LINKEDIN_PASSWORD="your-secure-password" LINKEDIN_USERNAME="your-profile-slug" ``` ### 4. First-Run Authentication ```bash uv run linkedin-mcp-pro-max --login ``` ### 5. Connect to Claude Desktop (or any MCP client) Add to your `claude_desktop_config.json`: ```json { "mcpServers": { "linkedin-mcp-pro-max": { "command": "/home/naimul/.local/bin/uv", "args": [ "--directory", "/home/naimul/linkedin-mcp-pro-max", "run", "linkedin-mcp-pro-max" ] } } } ``` --- ## The MCP Toolkit (14 Unified Tools) | Category | Tool | Actions | Description | | :--- | :--- | :--- | :--- | | **Profile** | `profile` | `get`, `analyze`, `update`, `update_cover_image` | Manage deep profile data, AI analysis, and identity updates | | | `experience` | `add`, `update`, `delete` | Manage professional experience entries | | | `education` | `add`, `update`, `delete` | Manage education entries | | | `skills` | `add`, `delete` | Manage skills on your profile | | | `company` | - | Get detailed corporate metadata and insights | | **Jobs & Intel** | `job` | `search`, `details`, `recommended`, `apply` | Discover, analyze, and apply for job postings | | | `application` | `list`, `track`, `update` | Manage internal job application tracking | | **Content** | `create_linkedin_post` | - | Publish AI-generated posts autonomously | | | `interact_with_post` | `read`, `like`, `comment` | Engage with feed posts via URL | | **Documents** | `generate_resume` | - | Generate a professional resume from your profile | | | `tailor_resume` | - | Target your resume to match a specific Job ID | | | `generate_cover_letter` | - | Create a personalized contextual cover letter | | | `list_templates` | - | View all available document templates | | **System** | `server` | `restart` | Manage the MCP server lifecycle | --- ## Architecture Built on **Clean Architecture** with a one-way dependency rule and a **Unified Component Registry** that eliminates all manual wiring. ``` [tools/] → [services/] → [browser/actors/ + browser/scrapers/] ctx.my_svc manager.my_actor / manager.my_scraper ``` ### Directory Structure ``` 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) ``` ### The Zero-Config Flow At startup, `helpers/registry.py` scans `services/`, `browser/actors/`, and `browser/scrapers/` automatically: ``` discover_all() ├── services/*.py → SERVICE = ServiceMeta(...) → injected into AppContext ├── browser/actors/* → ACTOR = ActorMeta(...) → instantiated in BrowserManager └── browser/scrapers/ → SCRAPER = ScraperMeta(...) → instantiated in BrowserManager ``` No manual registration. No editing `app.py` or `manager.py`. --- ## Adding New Features > For the complete development pipeline, debugging guide, and working examples, see the **[Tool Development Guide](docs/develop_new_tool.md)**. A full feature (scraper + service + tool) requires exactly **3 new files**. No existing file is modified. **1. Browser Scraper** — `src/browser/scrapers/my_feature.py` ```python from helpers.registry import ScraperMeta class MyFeatureScraper: def __init__(self, page): ... async def scrape(self): ... SCRAPER = ScraperMeta(attr="my_feature_scraper", cls=MyFeatureScraper) ``` **2. Service** — `src/services/my_feature.py` ```python 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) ``` **3. Tool** — `src/tools/my_feature.py` ```python 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) ``` `app.py`, `manager.py`, `services/__init__.py`, `tools/__init__.py` — never touched. --- ```bash 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 ``` --- ## Documentation | Document | Description | | :--- | :--- | | [Tool Development Guide](docs/develop_new_tool.md) | Full pipeline: creating tools, services, actors, scrapers. Debugging guide. | | [Services README](src/services/README.md) | Service layer conventions and dependency rules | | [Actors README](src/browser/actors/README.md) | Actor conventions and browser interaction patterns | | [Schema README](src/schema/README.md) | Pydantic model conventions | --- <p align="center"> <i>Automating your professional identity smartly, securely, and seamlessly.</i><br> <b><a href="https://github.com/mdnaimul22/linkedin-mcp-pro-max">Report an Issue</a></b> </p>