# Quick Data for Windows MCP
> **Windows-optimized fork of [disler/quick-data-mcp](https://github.com/disler/quick-data-mcp) for Claude Desktop**
>
> **Universal data analytics capabilities for JSON/CSV files - now working seamlessly on Windows!**
[](https://www.python.org/downloads/)
[](https://www.microsoft.com/windows)
[](https://claude.ai/desktop)
[](https://github.com/disler/quick-data-mcp)
## 🚀 What This Does
This is a **Windows-optimized fork** of the excellent [quick-data-mcp](https://github.com/disler/quick-data-mcp) project by [@disler](https://github.com/disler).
The original project provides powerful MCP server capabilities for data analytics, and this fork specifically addresses Windows compatibility issues and Claude Desktop integration challenges.
**This is my first ever try at this. Please feel free to give suggestions and or criticisms. I loved the quick data mcp for claude code. There was nothing available like it for claude desktop so with the help of claude code we now have it.
**Key Improvements Over Original:**
- ✅ **Windows Path Handling** - Proper Windows file path support
- ✅ **Claude Desktop Ready** - Pre-configured batch launchers and setup
- ✅ **Dependency Management** - Automated installation scripts
- ✅ **Troubleshooting** - Complete guides for common Windows issues
### ✨ Key Features
- **Universal Data Support** - Works with any CSV/JSON file structure
- **Windows Path Optimization** - Handles Windows file paths correctly
- **Claude Desktop Integration** - Pre-configured for seamless setup
- **Automatic Schema Discovery** - Analyzes your data and suggests analyses
- **32+ Analytics Tools** - From basic stats to advanced ML features
- **Interactive Visualizations** - Create charts with Plotly
- **Memory Management** - Optimized for large datasets
## 🏁 Quick Start for Windows
### Prerequisites
- **Windows 10/11**
- **Python 3.9+** ([Download here](https://www.python.org/downloads/))
- **Claude Desktop** ([Download here](https://claude.ai/desktop))
### Installation
1. **Download or clone this repository:**
```bash
git clone https://github.com/Beaulewis1977/quick-data-for-windows-mcp.git
cd quick-data-for-windows-mcp
```
2. **Install dependencies:**
```cmd
install_dependencies.bat
```
3. **Test the server:**
```cmd
test_server.bat
```
4. **Configure Claude Desktop:**
Copy the fixed configuration to Claude Desktop:
```cmd
copy claude_desktop_config_fixed.json "%APPDATA%\Claude\claude_desktop_config.json"
```
**IMPORTANT:** Edit the config file and update the `cwd` path to your actual installation directory.
5. **Restart Claude Desktop**
### 🚨 Having Issues?
If you see `ModuleNotFoundError: No module named 'mcp'`, check the [TROUBLESHOOTING.md](TROUBLESHOOTING.md) guide.
## 💻 Usage in Claude Desktop
Once configured, start with this slash command in Claude Desktop:
```
/quick-data-windows
```
### Loading Your Data
```
Load my sales data: C:\Users\YourName\Documents\sales_data.csv as "sales"
```
### Basic Analysis
```
Show me correlations in the sales dataset
Create a bar chart of sales by region
Analyze the distribution of revenue column
```
### Advanced Analytics
```
Validate data quality for sales dataset
Compare sales dataset with marketing dataset
Generate dashboard with revenue trends and regional breakdown
```
## 🔧 Available Tools
### Dataset Management
- `load_dataset` - Load CSV/JSON files with automatic schema discovery
- `list_loaded_datasets` - View all datasets in memory
- `get_dataset_info` - Get detailed dataset information
- `clear_dataset` / `clear_all_datasets` - Memory management
### Core Analytics
- `segment_by_column` - Analyze categorical data segments
- `find_correlations` - Discover relationships between variables
- `analyze_distributions` - Statistical distribution analysis
- `detect_outliers` - Identify data anomalies
- `suggest_analysis` - AI-powered analysis recommendations
### Visualization
- `create_chart` - Generate interactive charts (bar, scatter, line, histogram)
- `generate_dashboard` - Multi-chart dashboards
### Advanced Analytics
- `validate_data_quality` - Comprehensive data quality scoring
- `compare_datasets` - Multi-dataset comparison analysis
- `merge_datasets` - Join datasets with flexible strategies
- `calculate_feature_importance` - ML feature importance analysis
- `export_insights` - Export results in multiple formats
## 📂 Supported File Formats
### CSV Files
- Standard CSV with headers
- Custom delimiters automatically detected
- UTF-8 encoding support
- Large file handling with sampling options
### JSON Files
- Flat JSON structures
- Nested JSON (automatically flattened)
- JSON Lines format
- Array of objects format
## 🛠️ Configuration
### Manual Configuration
If the automatic setup doesn't work, manually edit your Claude Desktop config:
**Location:** `%APPDATA%\Claude\claude_desktop_config.json`
```json
{
"mcpServers": {
"quick-data-windows": {
"command": "python",
"args": [
"C:\\path\\to\\your\\quick-data-for-windows-mcp\\main.py"
],
"cwd": "C:\\path\\to\\your\\quick-data-for-windows-mcp",
"env": {
"LOG_LEVEL": "INFO",
"PYTHONPATH": "C:\\path\\to\\your\\quick-data-for-windows-mcp\\src"
}
}
}
}
```
### Alternative: Using UV Package Manager
If you prefer UV (recommended for Python dependency management):
```json
{
"mcpServers": {
"quick-data-windows": {
"command": "uv",
"args": [
"--directory",
"C:\\path\\to\\your\\quick-data-for-windows-mcp",
"run",
"python",
"main.py"
]
}
}
}
```
## 🧪 Testing the Server
Test the server standalone (before Claude Desktop integration):
```bash
python main.py
```
Expected output:
```
Quick Data for Windows MCP v1.0.0
Server running on stdio...
```
## 📊 Example Workflows
### Sales Data Analysis
```
1. Load sales_data.csv as "sales"
2. Show correlations in sales dataset
3. Create bar chart of sales by product_category
4. Detect outliers in revenue column
5. Generate dashboard with top products and regional trends
```
### Data Quality Assessment
```
1. Load customer_data.csv as "customers"
2. Validate data quality for customers dataset
3. Analyze distributions for age column
4. Segment by customer_type column
```
## 🔍 Troubleshooting
### Common Issues
**"Module not found" errors:**
- Ensure Python is in your PATH
- Run `pip install -r requirements.txt` manually
- Check that PYTHONPATH is set correctly in config
**"File not found" errors:**
- Use full Windows paths: `C:\Users\...`
- Avoid relative paths like `.\data\file.csv`
- Check file permissions
**Claude Desktop not finding server:**
- Restart Claude Desktop after config changes
- Check config file syntax with JSON validator
- Verify file paths are correct (no typos)
### Getting Help
1. Check that Python 3.9+ is installed: `python --version`
2. Verify dependencies: `pip list | findstr pandas`
3. Test server manually: `python main.py`
4. Check Claude Desktop logs for errors
## 🤝 Contributing
This is a community-driven Windows adaptation of the original quick-data-mcp project. Contributions welcome!
### Development Setup
```bash
# Clone and setup
git clone https://github.com/Beaulewis1977/quick-data-for-windows-mcp.git
cd quick-data-for-windows-mcp
# Install development dependencies
pip install -r requirements.txt
pip install pytest black ruff
# Run tests (when implemented)
pytest tests/
```
## 📝 License
MIT License - see LICENSE file for details.
## 🙏 Acknowledgments
**This project is a Windows-optimized fork of the original [quick-data-mcp](https://github.com/disler/quick-data-mcp) by [@disler](https://github.com/disler).**
### Original Project Credits
- **Original Author:** [@disler](https://github.com/disler)
- **Original Repository:** [disler/quick-data-mcp](https://github.com/disler/quick-data-mcp)
- **Original Purpose:** MCP server for data analytics with Claude Code
- **License:** MIT (maintained in this fork)
### Windows Fork Contributions
- **Windows Compatibility:** [@Beaulewis1977](https://github.com/Beaulewis1977)
- **Claude Desktop Integration:** Community-driven improvements
- **Troubleshooting & Documentation:** Enhanced for Windows users
### Technology Stack
- **Model Context Protocol:** [Anthropic](https://anthropic.com)
- **Data Processing:** pandas, numpy, plotly, scikit-learn
- **Platform:** Optimized for Windows + Claude Desktop
**⭐ Please star both repositories:**
- [Original Project](https://github.com/disler/quick-data-mcp) - For the core innovation
- [This Fork](https://github.com/Beaulewis1977/quick-data-for-windows-mcp) - For Windows support
Special thanks to [@disler](https://github.com/disler) for creating the foundational work that made this Windows adaptation possible!
## 🔗 Links
- [Claude Desktop](https://claude.ai/desktop)
- [Model Context Protocol](https://modelcontextprotocol.io/)
- [Original Quick Data MCP](https://github.com/disler/quick-data-mcp)
- [Python for Windows](https://www.python.org/downloads/windows/)
---
**This is my first ever try at this. Please feel free to give suggestions and or criticisms. I loved the quick data mcp for claude code. There was nothing available like it for claude desktop so with the help of claude code we now have it.
**Ready to analyze your data with AI? Load a CSV and start exploring! 🚀**
