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ProduckAI MCP Server

Python 3.11+ License: MIT MCP Protocol Code style: black Community

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 PRDsβ€”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

  • πŸ”§ Engineers build together - Improve clustering algorithms, add integrations, enhance AI prompts

  • πŸ“š Community grows knowledge - Document best practices, share PRD templates, teach new PMs

This isn't just a toolβ€”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

πŸ“₯ 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

πŸ“„ 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

πŸ”„ JIRA Integration

  • Bidirectional Sync - Issues ↔ Feedback

  • Auto-Priority - VOC score β†’ JIRA priority

  • Issue Creation - Generate epics from insights

  • Linkage Tracking - Trace feedback to issues


πŸš€ Quick Start

Prerequisites

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"

πŸ› οΈ Available Tools (50 Total)

πŸ“₯ 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

βš™οΈ 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

πŸ” 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

πŸ“„ 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

πŸ₯ Management (11 tools)

  • Status checks, sync monitoring, health checks, configuration

πŸ“Š Quick Reference

Integration

Setup Time

Cost/Month

Key Features

Slack

10 min

$1-2

AI classification, delta sync, bot filtering

Google Drive

15 min

$5-10

Multi-format, comments, auto-detect

Zoom

10 min

$3-4

Auto-download, AI analysis, sentiment

JIRA

5 min

Free

Bidirectional, VOC priority, evidence

CSV

0 min

Free

Bulk upload, templates, quick capture

Feature

Time

Cost

Output

Clustering (100 items)

1-2 min

$0.20

Themes & insights

VOC Scoring (100 items)

10 sec

$0.01

Priority ranking (0-100)

PRD Generation

10-15 sec

$0.05-0.10

Strategic document


πŸ“– 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.


πŸ—οΈ Architecture

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ Data Sources β”‚ Slack, Drive, Zoom, JIRA, CSV β””β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β–Ό β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ MCP Server β”‚ 50 tools, state management, AI classification β”‚ (This Package) β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β–Ό β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ ProduckAI API β”‚ Clustering, insights, embeddings β”‚ (Optional) β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”˜ β”‚ β–Ό β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ Claude Desktop β”‚ Natural language interface β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

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


πŸ§ͺ 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.


πŸ” 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.


πŸ“š Documentation


πŸ§‘β€πŸ’» 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.


πŸ› 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:

  • πŸ“– Documentation improvements

  • πŸ› Bug fixes and testing

  • ✨ New integration sources

  • 🌍 Internationalization

  • 🎨 UI/UX improvements


πŸ“Š 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


πŸ“„ License

MIT License - see LICENSE for details.


πŸ™ Acknowledgments



⭐ Star History

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


πŸ“§ Contact & Community

Get in Touch

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:

  • πŸ”Œ Integration enhancements - New data sources (Linear, Notion, Confluence, etc.)

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

  • πŸ“Š Analytics & metrics - New VOC scoring dimensions, priority frameworks

  • πŸ“ 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


Made with ❀️ by the ProduckAI community

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security - not tested
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license - permissive license
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quality - not tested

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