ProduckAI MCP Server

Transform scattered voice of customer feedback into actionable insights using AI-powered analysis and seamless Claude Desktop integration.

🌟 What is ProduckAI?

ProduckAI MCP Server brings enterprise-grade product feedback analysis directly into your AI workflows. Seamlessly integrate with Claude Desktop to analyze customer feedback, generate insights, prioritize features, and create executive-ready PRDs—all using natural language.

Key Value Proposition

• 70% faster Scattered VOC -> AI-powered generation

• Multi-source ingestion: Slack, Google Drive, Zoom, JIRA, CSV

• Smart prioritization: 6-dimension VOC scoring

• Evidence-backed decisions: Every PRD linked to customer quotes

• 50 specialized tools: Complete workflow from collection to execution

Why Open Source?

Product management is evolving with AI, but most tools are closed source and expensive. This project exists to democratize AI-powered product management for teams of all sizes.

By open sourcing this MCP server, we're creating a platform where:

• 🤝 PMs share learnings - Your feedback analysis insights help others prioritize better

• 🔧 Engineers build together - Improve clustering algorithms, add integrations, enhance AI prompts

• 📚 Community grows knowledge - Document best practices, share PRD templates, teach new PMs

This isn't just a tool—it's a movement to make product management more data-driven, evidence-based, and accessible to everyone.

If you're a PM who's ever struggled with feedback overload, or an engineer building tools for PMs, this project is for you. Contribute,learn, and help shape the future of AI-assisted product management.

✨ Features

📥 Multi-Source Feedback Collection

• Slack - Auto-sync channels with AI-powered customer detection

• Google Drive - Process docs, PDFs with OCR

• Zoom - Auto-fetch recordings, AI transcript analysis

• JIRA - Bidirectional sync with issue tracking

• CSV/Manual - Bulk upload or quick capture

🧠 AI-Powered Analysis

• Semantic Clustering - Group similar feedback automatically

• Insight Generation - AI creates actionable themes

• Sentiment Detection - Identify urgent vs nice-to-have

• Customer Attribution - Auto-match feedback to customers

🎯 Smart Prioritization

• VOC Scoring - 6-dimension scoring (0-100):

  • Customer Impact (30%) - Tier, revenue, strategic

  • Frequency (20%) - How often mentioned

  • Recency (15%) - How recent

  • Sentiment (15%) - Urgency level

  • Theme Alignment (10%) - Strategic fit

  • Effort (10%) - Implementation complexity

📄 PRD Generation

• AI-Powered PRDs - Strategic documents from insights

• Evidence-Based - Includes direct customer quotes

• Segment-Aware - Tailored for Enterprise vs SMB

• Risk Assessment - Effort-based implementation risks

• Version Tracking - PRD history and updates

🔄 JIRA Integration

• Bidirectional Sync - Issues ↔ Feedback

• Auto-Priority - VOC score → JIRA priority

• Issue Creation - Generate epics from insights

• Linkage Tracking - Trace feedback to issues

🚀 Quick Start

Prerequisites

• Python 3.11+

• Anthropic API Key (get one here)

• Claude Desktop (download)

Installation

pip install produckai-mcp-server

Configuration

1. Create environment file:

   cp .env.example .env
   # Edit .env and add your ANTHROPIC_API_KEY

2. Configure Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):

   {
     "mcpServers": {
       "produckai": {
         "command": "produckai-mcp",
         "env": {
           "ANTHROPIC_API_KEY": "your-api-key-here"
         }
       }
     }
   }

3. Restart Claude Desktop

First Use

Try these commands in Claude:

"Upload the demo feedback CSV at ./demo-data/feedback.csv"
"Run clustering and show me the top themes"
"Calculate VOC scores and show top 5 insights"
"Generate a PRD for the highest-priority insight"

🛠️ Available Tools (50 Total)

📥 Ingestion (21 tools)

• Slack: setup, sync channels, tag customers, bot filters

• Google Drive: setup, browse, sync folders, preview, processing config

• Zoom: setup, sync recordings, analyze meetings, insights, customer linking

• JIRA: setup, browse projects, bidirectional sync, mapping, reports

• Manual: CSV upload, Zoom transcript, raw capture, templates

⚙️ Processing (4 tools)

• run_clustering - Generate themes and insights

• generate_embeddings - Create vector embeddings

• get_themes - List all themes

• get_theme_details - Deep-dive on theme

🔍 Query (4 tools)

• search_insights - Natural language search

• get_insight_details - Full insight data

• search_feedback - Search raw feedback

• get_customer_feedback - Customer-specific view

🎯 VOC Scoring (4 tools)

• calculate_voc_scores - Score feedback/themes

• get_top_feedback_by_voc - Priority-ranked list

• configure_voc_weights - Customize algorithm

• get_voc_trends - Track changes over time

📄 PRD Generation (6 tools)

• generate_prd - Create PRD from insight

• list_prds - Browse generated PRDs

• get_prd - View full PRD

• update_prd_status - Workflow tracking

• regenerate_prd - Update after changes

• export_prd - Export to markdown

🏥 Management (11 tools)

• Status checks, sync monitoring, health checks, configuration

📊 Quick Reference

📖 Complete Workflow Example

Weekly Feedback Triage (20 minutes)

# Monday: Collect feedback
"Sync Slack #customer-feedback channel for the last 7 days"
"Sync Zoom recordings from the past week"
"Upload the quarterly feedback CSV"

# Tuesday: Analyze
"Run clustering to identify themes"
"Show me the top 10 themes by feedback count"

# Wednesday: Prioritize
"Calculate VOC scores for all insights"
"Show me the top 5 highest-priority insights"

# Thursday: Document
"Generate a PRD for the top insight about API rate limiting"
"Export the PRD to ~/Documents/PRDs/"

# Friday: Execute
"Sync the top 3 insights to JIRA project PROD"
"Show JIRA sync status"

Result: 3 executive-ready PRDs, synced to JIRA, evidence-backed by customer feedback.

🏗️ Architecture

┌─────────────────┐
│  Data Sources   │  Slack, Drive, Zoom, JIRA, CSV
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  MCP Server     │  50 tools, state management, AI classification
│  (This Package) │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  ProduckAI API  │  Clustering, insights, embeddings
│  (Optional)     │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  Claude Desktop │  Natural language interface
└─────────────────┘

Deployment Model: Local single-user (each PM runs their own instance)

🧪 Demo Data

Try ProduckAI with sample data:

# Generate demo data (50 feedback items)
python scripts/generate_demo_data.py

# In Claude:
"Upload demo-data/feedback.csv"
"Run clustering"
"Generate PRD for top insight"

See demo-data/README.md for details.

🔐 Integration Setup

Slack

1. Create Slack App: https://api.slack.com/apps

2. Add scopes: channels:history, channels:read, users:read

3. Install to workspace

4. In Claude: "Setup Slack integration"

Google Drive

1. Create GCP project: https://console.cloud.google.com

2. Enable Google Drive API

3. Create OAuth credentials (Desktop app)

4. In Claude: "Setup Google Drive integration"

JIRA

1. Generate API token: https://id.atlassian.com/manage/api-tokens

2. In Claude: "Setup JIRA integration with server URL, email, and token"

Zoom

1. Create OAuth app: https://marketplace.zoom.us/develop/create

2. Add scope: recording:read:admin

3. In Claude: "Setup Zoom integration"

See docs/ for detailed setup guides.

📚 Documentation

• Installation Guide

• Quick Start Guide

• Integration Setup

• End-to-End Workflow

• Open Source Roadmap

• Phase Implementation Docs

  • Phase 5: JIRA & VOC

  • Phase 6: PRD Generation

• PRD Generation Prompt

• Contributing Guide

🧑‍💻 Development

Setup

# Clone repository
git clone https://github.com/produckai/produckai-mcp-server.git
cd produckai-mcp-server

# Create virtual environment
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# Install in development mode
pip install -e ".[dev]"

Testing

# Run tests
pytest

# Run with coverage
pytest --cov

# Run linting
ruff check .

# Format code
black .

# Type checking
mypy src/

Code Quality

We use:

• Black for code formatting

• Ruff for linting

• MyPy for type checking

• Pytest for testing

See CONTRIBUTING.md for guidelines.

🐛 Troubleshooting

MCP Server Not Appearing in Claude

1. Check config: cat ~/Library/Application\ Support/Claude/claude_desktop_config.json

2. Verify command: which produckai-mcp

3. Check logs: tail -f ~/.produckai/logs/mcp-server.log

4. Restart Claude Desktop completely

API Connection Issues

# Test Anthropic API
export ANTHROPIC_API_KEY=your-key
python -c "from anthropic import Anthropic; print(Anthropic().messages.create(model='claude-3-haiku-20240307', max_tokens=10, messages=[{'role':'user','content':'hi'}]))"

Common Issues

• "Command not found" - Ensure produckai-mcp is in PATH

• "Connection refused" - Check API keys are set

• "Import error" - Reinstall: pip install --force-reinstall produckai-mcp-server

See docs/TROUBLESHOOTING.md for more.

🤝 Contributing

We welcome contributions! Here's how:

1. Fork the repository

2. Create a feature branch: git checkout -b feature/your-feature

3. Commit your changes: git commit -m "Add feature"

4. Push to your fork: git push origin feature/your-feature

5. Open a Pull Request

See CONTRIBUTING.md for detailed guidelines.

Areas We Need Help:

• 📖 Documentation improvements

• 🐛 Bug fixes and testing

• ✨ New integration sources

• 🌍 Internationalization

• 🎨 UI/UX improvements

📊 Performance & Cost

Speed

• Feedback sync: ~1-2 seconds per item

• Clustering: ~1-2 minutes for 100 items

• PRD generation: ~10-15 seconds per PRD

Cost (AI APIs)

• Embeddings: ~$0.01 per 100 items (OpenAI)

• Clustering/Insights: ~$0.20 per 100 items (Claude Haiku)

• PRD Generation: ~$0.05-0.10 per PRD (Claude Sonnet)

• Monthly (100 PRDs): ~$5-10 total

📄 License

MIT License - see LICENSE for details.

🙏 Acknowledgments

• Built with MCP SDK

• Powered by Anthropic Claude

• Inspired by product teams everywhere

🔗 Links

• Issues - Report bugs

• Discussions - Ask questions

• Changelog - Release notes

• Security Policy - Report vulnerabilities

⭐ Star History

If you find this project useful, please star it! It helps others discover ProduckAI.

📧 Contact & Community

Get in Touch

• Creator: Rohit Saraf (rohitsaraff33@gmail.com)

• Issues: GitHub Issues - Bug reports, feature requests

• Discussions: GitHub Discussions - Questions, ideas, showcases

Vision & Community

This project was built for product managers, by product managers. The goal is to create a thriving open source community where builders enhance integrations, improve insight generation logic, and share learnings so the entire PM community benefits.

We especially welcome contributions in:

• 🔌 Integration enhancements - New data sources (Linear, Notion, Confluence, etc.)

• 🧠 Insight generation - Advanced clustering algorithms, sentiment analysis improvements

• 📊 Analytics & metrics - New VOC scoring dimensions, priority frameworks

• 📝 PRD templates - Industry-specific or company-specific variations

• 🌍 Localization - Multi-language support for global teams

Whether you're a PM improving your workflow or an engineer building better tools for PMs, your contributions help everyone in the product community. Let's build this together!

Built with ❤️ by Rohit Saraf and the product management community

Made with ❤️ by the ProduckAI community