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Produckai MCP Server

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

Unclaimed MIT last commit 10 months ago devtools
53Fair

Scored 6 days ago · breakdown

About Produckai MCP Server

Produckai MCP Server is an MCP server published by rohitsaraff33-bit in the Developer Tools category: transform scattered voice of customer into actionable insights using AI-powered analysis and seamless Claude Desktop integration.

The repository has 1 stars and 0 forks, with the last commit 10 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.

Install

From source
git clone https://github.com/rohitsaraff33-bit/produckai-mcp-server

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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  • ✓README presentThe repository ships documentation.
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  • !Dependencies pinnedNo lockfile. Installs can pull different code over time.
  • ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
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Releases

v0.7.0ProduckAI MCP Server v0.7.0 · 3 Dec 2025🎉 Initial Release: ProduckAI MCP Server v0.7.0 Transform scattered voice of customer feedback into actionable insights using AI-powered analysis and seamless Claude Desktop integration. ✨ Features 📥 Multi-Source Feedback Collection Slack -…

README

ProduckAI MCP Server

MCP Protocol 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 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

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

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

📖 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


🧑‍💻 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


🔗 Links


⭐ Star History

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


📧 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:

  • 🔌 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

README fetched from the repository 6 days ago. The original is authoritative.

Questions

About Produckai MCP Server

How do I install Produckai MCP Server?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Produckai MCP Server safe to use with an AI agent?

Its trust score is 53 out of 100 (fair). It passes 4 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Produckai MCP Server still maintained?

The last commit was 10 months ago. That's long enough that you should check whether the maintainer is responding to issues before depending on it.