DevRel MCP 🚀

MCP server for tracking developer relations content, events, and impact analytics

A comprehensive MCP (Model Context Protocol) server that helps developer advocates track content performance, event outcomes, and measure career impact with advanced analytics.

Features

📹 Content Tracking

• YouTube Integration: Seamless video tracking with track_youtube_video
• Auto-Tag Detection: Smart tagging from titles and descriptions
• AI Summaries: Store and search video summaries and transcripts
• Flexible Metrics: Views, likes, comments with string/integer support
• Multi-Platform: YouTube, blogs, social media, code repositories

🎪 Event Management

• Workshops: Attendee count, feedback scores, materials
• Speaking Engagements: Audience size, satisfaction ratings, follow-ups
• Conferences: ROI tracking, lead generation, networking outcomes
• Meetups: Community impact, recurring attendance, partnerships

📊 Analytics & Insights

• Smart Search: Text search across titles, descriptions, and summaries
• Performance Trends: Growth metrics and engagement analytics
• ROI Calculations: Event cost/benefit analysis with lead tracking
• Export Options: CSV and JSON formats for external analysis
• Natural Language: Search with queries like "Find my AWS videos"

Quick Start

Installation

git clone https://github.com/labeveryday/devrel-mcp
cd devrel-mcp
uv sync

Usage

# Start the MCP server (from src directory)
cd src && uv run python server.py

# Or use the installed command
uv run devrel-mcp

# Connect via Claude Code or compatible MCP client
# Server runs on STDIO transport for MCP protocol

Connecting to MCP Clients

Claude Code

# Add the MCP server to Claude Code
claude mcp add devrel-mcp --scope user \
  -- uv --directory /path/to/devrel-mcp run src/server.py

# Replace /path/to/devrel-mcp with your actual project path
# Example: 
# claude mcp add devrel-mcp --scope user \
#   -- uv --directory ~/projects/devrel-mcp run src/server.py

Claude Desktop

Add to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "devrel-mcp": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/devrel-mcp",
        "run",
        "src/server.py"
      ],
      "env": {
        "UV_SYSTEM_PYTHON": "1"
      }
    }
  }
}

Q CLI

Add to your Q CLI configuration:

{
  "mcp": {
    "servers": {
      "devrel-mcp": {
        "command": "uv",
        "args": [
          "--directory",
          "/path/to/devrel-mcp", 
          "run",
          "src/server.py"
        ]
      }
    }
  }
}

Database

• TinyDB: Modern JSON-based database (devrel.json) with native Python types
• Auto-created: Database is created automatically on first run
• No SQL Required: Simple JSON storage with powerful search capabilities
• Git Safe: Database files are excluded from version control via .gitignore
• Privacy Protected: .cursorignore keeps sensitive data from AI tools
• Portable: Single JSON file contains all your DevRel data

Sample Usage with DevRel MCP

Once connected to your MCP client, you can use natural language prompts to manage your DevRel activities:

📹 Content Tracking

Prompt: "Track this video: https://youtu.be/8gTpgWru0Wg"

DevRel MCP automatically extracts video data from YouTube MCP and creates:

DevRel MCP Response:

{
  "success": true,
  "content": {
    "id": 1,
    "title": "Building AI agents with Claude in Amazon Bedrock",
    "url": "https://youtu.be/8gTpgWru0Wg",
    "auto_detected_tags": ["aws", "claude", "ai", "bedrock", "workshop"],
    "views": 15740,
    "likes": 242,
    "comments": 28,
    "summary": "AI-generated summary from video transcript...",
    "platform": "YouTube"
  }
}

Prompt: "Do I have any content on MCP?" → Smart search finds: "Building Agents with Amazon Nova Act and MCP..."

🎪 Event Management

Prompt: "I'm speaking at re:Invent next month. Create an event for my workshop 'Serverless at Scale' on December 3rd at the Venetian in Las Vegas."

DevRel MCP Response:

{
  "success": true,
  "event": {
    "id": 1,
    "type": "workshop",
    "title": "Serverless at Scale",
    "date": "2025-12-03",
    "location": "Venetian, Las Vegas",
    "created_at": "2025-08-26T10:35:00"
  }
}

Prompt: "Update event ID 1 - we had 75 attendees, satisfaction score of 8.7, and generated 12 leads"

📊 Analytics & Reporting

Prompt: "Show me my content performance for the last 30 days"

DevRel MCP Response:

{
  "period_days": 30,
  "overview": {
    "total_content": 8,
    "total_views": 15750,
    "avg_views_per_content": 1968.8,
    "overall_engagement_rate": 4.2
  },
  "top_performers": {
    "most_viewed": [
      {
        "title": "AWS Lambda Best Practices",
        "views": 2500,
        "type": "video"
      }
    ]
  }
}

Prompt: "Generate my quarterly report and export it to CSV"

DevRel MCP Response:

{
  "success": true,
  "file_path": "/tmp/devrel_analytics_20250826_103045.csv",
  "message": "Quarterly report exported to CSV"
}

📈 Advanced Analytics

Prompt: "Calculate ROI for my events in the last 90 days"

DevRel MCP Response:

{
  "financial_summary": {
    "total_events": 5,
    "total_revenue": 7500.00,
    "total_costs": 2300.00,
    "net_revenue": 5200.00,
    "roi_percentage": 226.09
  },
  "impact_summary": {
    "total_attendees": 425,
    "total_leads_generated": 67,
    "avg_satisfaction_score": 8.4
  }
}

Prompt: "Show me my growth trends over the last 6 months"

💡 More Example Prompts

Content Management:

• "List all my video content from the past quarter"
• "Delete the blog post with ID 5"
• "Show me all content tagged with 'serverless'"

Event Tracking:

• "Find all my conference talks from 2024"
• "What's my average satisfaction score for workshops?"
• "List events where I generated more than 10 leads"

Quick Analytics:

• "What's my best performing content this month?"
• "Export my Q4 analytics to JSON format"
• "Compare my content performance to last quarter"

Architecture

• FastMCP: Modern Python-based MCP server with automatic tool generation
• TinyDB: JSON-based document database with native Python data types
• Pydantic: Type-safe data models and validation with flexible input handling
• Union Types: Accepts both string and native types for seamless MCP integration
• Smart Search: Full-text search across titles, descriptions, and AI summaries
• Privacy-First: Comprehensive .gitignore and .cursorignore protection

What's Included

✅ Complete DevRel Tracking System

• 📊 20+ MCP Tools - Comprehensive content and event management with search
• 🗃️ TinyDB Database - Modern JSON storage with native Python types
• 🎥 YouTube Integration - One-command video tracking with auto-tagging
• 🔍 Smart Search - Find content by text, tags, or AI-generated summaries
• 📝 AI Summary Support - Store and search video summaries and transcripts
• 📈 Advanced Analytics - Performance metrics, ROI analysis, quarterly reports
• 📤 Export Capabilities - CSV and JSON export for all analytics
• 🔒 Privacy Protection - Comprehensive gitignore and AI context protection
• 🚀 FastMCP Server - Modern Python with flexible Union type handling

Available Tools

The MCP server provides 20+ tools for comprehensive DevRel tracking:

YouTube & Content Management:

• track_youtube_video - 🎥 NEW: One-command YouTube tracking with auto-tagging
• add_content_summary - 📝 NEW: Add AI-generated summaries to existing content
• create_content - Track videos, blogs, social posts, code repos
• get_content - Retrieve specific content details
• list_content - Browse all content with filtering
• update_content_metrics - Update views, likes, shares, etc.
• delete_content_item - Remove content items

Smart Search:

• search_content - 🔍 ENHANCED: Text search in titles, descriptions, and summaries
• search_events - 🔍 ENHANCED: Find events by text, location, organizer, tags

Event Management:

• create_event - Log workshops, conferences, meetups
• get_event - Get detailed event information
• list_events - Browse all events with filtering
• update_event_outcomes - Post-event metrics and feedback
• delete_event_item - Remove events

Analytics & Reporting:

• get_analytics_summary - Period-based performance insights
• get_content_performance - Comprehensive content analytics with trends
• get_event_roi_analysis - ROI and financial impact analysis
• generate_quarterly_report - Complete quarterly performance reports
• export_analytics_csv - Export reports to CSV format
• export_analytics_json - Export reports to JSON format
• get_impact_trends - Multi-month trend analysis and growth metrics

See IMPLEMENTATION_PLAN.md for detailed roadmap.

🎉 Recent Improvements

Version 0.4.0 - Major Architecture Upgrade

🏗️ Database Migration

• ✅ SQLite → TinyDB: Modern JSON storage with native Python types
• ✅ No More JSON Strings: Tags and metadata stored as native lists/objects
• ✅ Flexible Input: Accepts both strings ("15694") and integers (15694)
• ✅ Better Performance: Document-based storage optimized for DevRel data

🎥 YouTube Integration

• ✅ track_youtube_video(): One function handles complete YouTube workflow
• ✅ Auto-Tag Detection: Smart extraction from titles/descriptions (AWS, Claude, AI, etc.)
• ✅ Summary Support: Store AI-generated video summaries and transcripts
• ✅ Seamless MCP Integration: Works perfectly with YouTube MCP servers

🔍 Search Overhaul

• ✅ Fixed Text Search: Proper substring matching instead of regex
• ✅ Case-Insensitive: "MCP", "mcp", "Mcp" all work
• ✅ Multi-Field Search: Searches titles, descriptions, AND summaries
• ✅ Natural Language: "Do I have content on MCP?" → finds results

🔒 Privacy & Security

• ✅ Enhanced .gitignore: Protects database files, exports, personal notes
• ✅ .cursorignore: Keeps sensitive data from AI context
• ✅ PRIVACY.md: Clear documentation of what stays private

🛠️ Developer Experience

• ✅ Union Type Support: Union[str, int, None] for flexible MCP input
• ✅ Better Error Handling: Clear validation messages
• ✅ Comprehensive Testing: All functionality validated
• ✅ Modern Python: Type hints, async support, clean architecture

Use Cases

📊 Quarterly Reviews

• Generate comprehensive reports with generate_quarterly_report
• Export analytics to CSV/JSON for performance discussions
• Track content performance and event ROI over time

📈 Content Strategy

• Analyze top-performing content with get_content_performance
• Identify trends and growth patterns with get_impact_trends
• Optimize content mix based on engagement analytics

💰 Event Planning & ROI

• Track speaker fees, travel costs, and lead generation
• Calculate satisfaction scores and follow-up conversion rates
• Measure true event impact beyond just attendance

Contributing

Built for developer advocates! New features can be added by creating FastMCP tool functions with proper docstrings.

License

MIT License - see LICENSE for details.

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Built for developer advocates to measure and maximize professional impact 🚀