CompText MCP Server

# 🚀 Launch Plan - CompText MCP Server ## Status: READY TO LAUNCH ✅ **Version:** 1.0.0 **Launch Date:** 2024-12-04 **Target:** AI/LLM Developer Community --- ## 🎯 Launch Objectives 1. **Primary Goal:** 500+ GitHub Stars in first month 2. **Secondary Goal:** 50+ active users 3. **Tertiary Goal:** 10+ contributors --- ## ✅ Pre-Launch Checklist ### Repository - [x] Professional README with badges - [x] Complete documentation (7 docs files) - [x] Working examples and tutorials - [x] CI/CD pipeline configured - [x] Tests passing (12/12) - [x] LICENSE (MIT) - [x] CODE_OF_CONDUCT.md - [x] CONTRIBUTING.md - [x] SECURITY.md ### Code Quality - [x] All core features working - [x] Error handling implemented - [x] Logging configured - [x] Performance optimized (LRU cache) - [x] Type hints added ### Deployment - [x] Docker support - [x] Railway config - [x] Multi-platform configs - [x] Setup scripts (macOS/Linux/Windows) ### Marketing Materials - [x] Repository description - [x] Social media templates (see below) - [x] Demo video script - [x] Blog post outline --- ## 📱 Social Media Templates ### Twitter/X Post ``` 🚀 Launching CompText MCP Server v1.0! Reduce LLM token usage by 90-95% with domain-specific commands. ✅ Universal: Claude, Perplexity, Cursor, ChatGPT ✅ Easy Setup: One command installation ✅ Production Ready: Docker, Railway, CI/CD 🔗 https://github.com/ProfRandom92/comptext-mcp-server #AI #MCP #LLM #OpenSource #DevTools ``` ### LinkedIn Post ``` Excited to announce CompText MCP Server v1.0! 🚀 After months of development, we're releasing an open-source solution that reduces LLM token usage by 90-95% through domain-specific language compression. Key Features: • Universal compatibility (Claude, Perplexity, Cursor, ChatGPT, and more) • Native MCP Protocol + REST API • Production-ready with Docker, CI/CD, comprehensive docs • 7 powerful tools for managing your DSL codex Perfect for: - AI developers managing large codebases - Teams standardizing LLM interactions - Anyone looking to optimize token costs Check it out: https://github.com/ProfRandom92/comptext-mcp-server #ArtificialIntelligence #OpenSource #DeveloperTools #MachineLearning ``` ### Reddit Posts #### r/MachineLearning ``` Title: [P] CompText MCP Server - Reduce LLM Token Usage by 90-95% Hey r/MachineLearning! I've been working on a solution to a problem many of us face: massive token consumption when working with LLMs. CompText MCS Server provides a domain-specific language approach that compresses common patterns. **What it does:** - Stores reusable command patterns in Notion - Provides universal access via MCP Protocol & REST API - Works with Claude, Perplexity, Cursor, ChatGPT, and more **Real impact:** Instead of sending 25,000 tokens of boilerplate, you send a 500-token reference. That's 95% reduction. **Tech Stack:** - Python 3.10+ - FastAPI for REST - MCP SDK for native integration - Notion as backend - Docker-ready Fully open source (MIT license), production-ready with CI/CD, tests, and comprehensive docs. GitHub: https://github.com/ProfRandom92/comptext-mcp-server Would love feedback from the community! ``` #### r/programming ``` Title: Built an open-source MCP server for token-efficient LLM interactions After hitting token limits repeatedly while building AI-powered dev tools, I created CompText MCP Server. **Problem:** Repeatedly sending the same context/instructions to LLMs wastes tokens and money. **Solution:** Store reusable patterns in a searchable codex, reference them by ID. **Why MCP?** Model Context Protocol is the new standard for AI tool integration. Works natively with Claude, Cursor, and growing ecosystem. **Why Notion?** Your team already uses it, and it's a great UI for managing command libraries. Repo: https://github.com/ProfRandom92/comptext-mcp-server Setup takes 5 minutes. Includes Docker, Railway deployment, CI/CD, the works. MIT licensed, PRs welcome! ``` #### r/LocalLLaMA ``` Title: CompText MCP Server - Token-efficient DSL for any LLM For those running local models where context windows matter: CompText MCP Server lets you store common prompts/patterns externally and reference them. Instead of: "Here's my entire coding style guide... [25,000 tokens]" You send: "Use [Code-Style-Guide-v2]" [50 tokens] Works with: - Local models (LM Studio, Jan, Ollama) - Cloud (Claude, GPT-4, Perplexity) - IDEs (Cursor, VS Code) Open source, easy Docker setup: https://github.com/ProfRandom92/comptext-mcp-server ``` ### Dev.to / Medium Blog Post Outline ```markdown # Building a Token-Efficient LLM Workflow with CompText MCP Server ## The Problem - Token costs adding up - Repeatedly sending same context - No standardization across team ## The Solution - Domain-Specific Language approach - MCP Protocol integration - Notion as knowledge base ## Implementation - Architecture overview - Code examples - Performance benchmarks ## Results - 90-95% token reduction - Faster response times - Better consistency ## Getting Started - 5-minute setup guide - Platform integrations - Best practices ## Conclusion - Open source, MIT licensed - Production ready - Community welcome [Link to GitHub] ``` --- ## 📊 Target Platforms ### Primary Channels 1. **GitHub** - Trending repositories - Topics: mcp, ai, llm, notion, python - README optimization for discovery 2. **Reddit** - r/MachineLearning (1.5M members) - r/programming (6M members) - r/LocalLLaMA (150K members) - r/ClaudeAI (50K members) - r/Notion (500K members) 3. **Twitter/X** - #AI #MCP #LLM hashtags - @ mentions: @AnthropicAI, @perplexity_ai - Dev community 4. **LinkedIn** - Professional AI/ML groups - Developer communities - Company page 5. **Dev Communities** - Dev.to - Hashnode - Hacker News (Show HN) - Product Hunt ### Secondary Channels 6. **Discord Servers** - Anthropic Discord - AI Dev communities - Open source communities 7. **YouTube** - Demo video - Tutorial series --- ## 📝 Content Calendar (Week 1) ### Day 1 (Launch Day) - [x] Push v1.0.0 tag - [ ] GitHub Release with notes - [ ] Reddit: r/MachineLearning - [ ] Twitter announcement - [ ] LinkedIn post - [ ] Dev.to article ### Day 2 - [ ] Reddit: r/programming - [ ] Hacker News (Show HN) - [ ] Product Hunt submission - [ ] Discord communities ### Day 3 - [ ] Reddit: r/LocalLLaMA - [ ] Follow-up tweets - [ ] Respond to all comments ### Day 4 - [ ] Reddit: r/ClaudeAI, r/Notion - [ ] Medium article - [ ] YouTube demo video ### Day 5-7 - [ ] Community engagement - [ ] Address issues/questions - [ ] First minor update if needed - [ ] Collect feedback for v1.1 --- ## 🎬 Demo Video Script (3 minutes) **[0:00-0:15] Hook** "What if you could reduce your LLM token usage by 95% without losing functionality? Let me show you how." **[0:15-0:45] Problem** - Show typical LLM interaction with massive context - Token counter showing high usage - Cost implications **[0:45-1:30] Solution** - Introduce CompText MCP Server - Show architecture diagram - Explain DSL approach **[1:30-2:30] Demo** - Quick setup (timelapse) - Show it working in Claude - Show it working in Perplexity - Show REST API in action **[2:30-3:00] Call to Action** - GitHub link - Star the repo - Try it yourself - Join the community --- ## 📊 Success Metrics ### Week 1 Targets - GitHub Stars: 100+ - Forks: 20+ - Issues opened: 10+ (shows engagement) - Reddit upvotes: 500+ (combined) - Twitter impressions: 10,000+ ### Month 1 Targets - GitHub Stars: 500+ - Active users: 50+ - Contributors: 5+ - Notion mentions: 10+ - Blog posts/articles: 5+ --- ## 👥 Community Building ### Immediate Actions 1. **Enable GitHub Discussions** 2. **Create Discord server** (optional) 3. **Set up email for contact** 4. **Prepare to respond quickly** to: - Issues - PRs - Questions - Feature requests ### Long-term 1. **Weekly updates** 2. **Monthly releases** 3. **Community calls** (if interest grows) 4. **Showcase** user implementations --- ## 🛠️ Post-Launch Improvements ### Version 1.1 (2 weeks) - [ ] User feedback implementation - [ ] Performance improvements - [ ] Additional platform support - [ ] Video tutorials ### Version 1.2 (1 month) - [ ] GraphQL API - [ ] WebSocket support - [ ] Enhanced search - [ ] Metrics dashboard --- ## 🆘 Repository Optimization ### GitHub Settings - [x] Description: "Token-efficient DSL for LLM interactions - Universal MCP Server & REST API" - [ ] Topics: mcp, ai, llm, notion, python, claude, perplexity, cursor, api, dsl - [ ] Website: Link to documentation - [ ] Enable Discussions - [ ] Enable Wikis (for community docs) - [ ] Social preview image (1280x640) ### SEO Keywords - Model Context Protocol - MCP Server - LLM Token Optimization - Claude AI Integration - Notion API - AI Developer Tools - Token-efficient prompts - Domain-Specific Language --- ## ✅ Launch Day Actions **Morning (9 AM CET)** 1. [ ] Create GitHub Release v1.0.0 2. [ ] Post to Twitter 3. [ ] Post to LinkedIn 4. [ ] Submit to r/MachineLearning **Afternoon (2 PM CET)** 5. [ ] Post to Dev.to 6. [ ] Submit to Hacker News 7. [ ] Post in Discord communities **Evening (6 PM CET)** 8. [ ] Respond to all comments 9. [ ] Address any issues 10. [ ] Engage with community **Before Bed** 11. [ ] Check metrics 12. [ ] Plan Day 2 actions --- **Ready to Launch!** 🚀 Let's make CompText MCP Server the go-to solution for token-efficient LLM interactions!