coldcoach
Think of it as your personal wingman for networking.
Core trick
MCP server pulls a target's recent X or LinkedIn posts and prompts an LLM to draft date-aware icebreaker messages.
Description
Think of it as your personal wingman for networking.
Say you’re at a big tech event—you spot someone across the room, you know they matter, maybe you’ve seen their posts on LinkedIn or X, but you have no idea how to break the ice.
You type in their name, and boom—our AI pulls their latest online vibe and gives you a bold opener plus a quick game plan to keep the conversation flowing.
No awkward small talk. Just instant confidence and real connections.
README excerpt
# Social Media Cold Outreach MCP Server A Model Context Protocol (MCP) server designed to help generate personalized engagement messages for Twitter/X and LinkedIn cold outreach. The server analyzes users' latest posts to create contextual ice-breaker messages for professional networking or casual engagement. ## 🎯 Purpose This MCP server helps AI assistants (like Le Chat, Claude, etc.) create personalized engagement messages for social media outreach by: - **Twitter/X**: Fetching latest tweets and generating witty, casual engagement messages - **LinkedIn**: Retrieving recent posts and creating professional, insightful connection requests - Analyzing post content with date awareness for relevance - Generating platform-appropriate messages that reference specific details from recent posts ## 🚀 Features - **Multi-Platform Support**: Separate tools for Twitter/X and LinkedIn - **Smart Content Analysis**: - Twitter: Fetches latest original tweets (skips retweets) - LinkedIn: Retrieves recent posts with full engagement metrics - **Date-Aware**: Includes posting dates for recency-based outreach - **Platform-Specific Messaging**: Tailored instructions for each platform's culture - **MCP Integration**: Works with any MCP-compatible AI assistant - **HTTP Transport**: Easy deployment with ngrok for cloud accessibility - **Apify Integration**: Uses reliable scrapers for both platforms ## 📋 Prerequisites - Python 3.10 or higher - [uv](https://github.com/astral-sh/uv) package ma