{"id":28719943,"url":"https://github.com/beaulewis1977/quick-data-for-windows-mcp","last_synced_at":"2026-04-14T06:04:26.461Z","repository":{"id":298212852,"uuid":"999209195","full_name":"Beaulewis1977/quick-data-for-windows-mcp","owner":"Beaulewis1977","description":"Windows-optimized MCP server for Claude Desktop providing universal data analytics capabilities","archived":false,"fork":false,"pushed_at":"2025-06-10T01:22:33.000Z","size":97,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-10T01:30:23.015Z","etag":null,"topics":["claude-desktop","csv","data-analytics","json","mcp","python","windows"],"latest_commit_sha":null,"homepage":"","language":"Batchfile","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Beaulewis1977.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-09T23:02:13.000Z","updated_at":"2025-06-10T01:22:36.000Z","dependencies_parsed_at":"2025-06-10T01:40:48.645Z","dependency_job_id":null,"html_url":"https://github.com/Beaulewis1977/quick-data-for-windows-mcp","commit_stats":null,"previous_names":["beaulewis1977/quick-data-for-windows-mcp"],"tags_count":2,"template":false,"template_full_name":null,"purl":"pkg:github/Beaulewis1977/quick-data-for-windows-mcp","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Beaulewis1977%2Fquick-data-for-windows-mcp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Beaulewis1977%2Fquick-data-for-windows-mcp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Beaulewis1977%2Fquick-data-for-windows-mcp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Beaulewis1977%2Fquick-data-for-windows-mcp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Beaulewis1977","download_url":"https://codeload.github.com/Beaulewis1977/quick-data-for-windows-mcp/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Beaulewis1977%2Fquick-data-for-windows-mcp/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":259929972,"owners_count":22933536,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["claude-desktop","csv","data-analytics","json","mcp","python","windows"],"created_at":"2025-06-15T06:06:13.205Z","updated_at":"2026-04-14T06:04:26.421Z","avatar_url":"https://github.com/Beaulewis1977.png","language":"Batchfile","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Quick Data for Windows MCP\n\n\u003e **Windows-optimized fork of [disler/quick-data-mcp](https://github.com/disler/quick-data-mcp) for Claude Desktop**\n\u003e \n\u003e **Universal data analytics capabilities for JSON/CSV files - now working seamlessly on Windows!**\n\n[![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)\n[![Windows](https://img.shields.io/badge/platform-Windows-blue.svg)](https://www.microsoft.com/windows)\n[![Claude Desktop](https://img.shields.io/badge/Claude-Desktop-purple.svg)](https://claude.ai/desktop)\n[![Original Project](https://img.shields.io/badge/fork-disler%2Fquick--data--mcp-green.svg)](https://github.com/disler/quick-data-mcp)\n\n## 🚀 What This Does\n\nThis 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). \n\nThe original project provides powerful MCP server capabilities for data analytics, and this fork specifically addresses Windows compatibility issues and Claude Desktop integration challenges.\n\n**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.\n\n**Key Improvements Over Original:**\n- ✅ **Windows Path Handling** - Proper Windows file path support\n- ✅ **Claude Desktop Ready** - Pre-configured batch launchers and setup\n- ✅ **Dependency Management** - Automated installation scripts\n- ✅ **Troubleshooting** - Complete guides for common Windows issues\n\n### ✨ Key Features\n\n- **Universal Data Support** - Works with any CSV/JSON file structure\n- **Windows Path Optimization** - Handles Windows file paths correctly\n- **Claude Desktop Integration** - Pre-configured for seamless setup\n- **Automatic Schema Discovery** - Analyzes your data and suggests analyses\n- **32+ Analytics Tools** - From basic stats to advanced ML features\n- **Interactive Visualizations** - Create charts with Plotly\n- **Memory Management** - Optimized for large datasets\n\n## 🏁 Quick Start for Windows\n\n### Prerequisites\n\n- **Windows 10/11**\n- **Python 3.9+** ([Download here](https://www.python.org/downloads/))\n- **Claude Desktop** ([Download here](https://claude.ai/desktop))\n\n### Installation\n\n1. **Download or clone this repository:**\n   ```bash\n   git clone https://github.com/Beaulewis1977/quick-data-for-windows-mcp.git\n   cd quick-data-for-windows-mcp\n   ```\n\n2. **Install dependencies:**\n   ```cmd\n   install_dependencies.bat\n   ```\n\n3. **Test the server:**\n   ```cmd\n   test_server.bat\n   ```\n\n4. **Configure Claude Desktop:**\n   \n   Copy the fixed configuration to Claude Desktop:\n   ```cmd\n   copy claude_desktop_config_fixed.json \"%APPDATA%\\Claude\\claude_desktop_config.json\"\n   ```\n   \n   **IMPORTANT:** Edit the config file and update the `cwd` path to your actual installation directory.\n\n5. **Restart Claude Desktop**\n\n### 🚨 Having Issues?\n\nIf you see `ModuleNotFoundError: No module named 'mcp'`, check the [TROUBLESHOOTING.md](TROUBLESHOOTING.md) guide.\n\n## 💻 Usage in Claude Desktop\n\nOnce configured, start with this slash command in Claude Desktop:\n\n```\n/quick-data-windows\n```\n\n### Loading Your Data\n\n```\nLoad my sales data: C:\\Users\\YourName\\Documents\\sales_data.csv as \"sales\"\n```\n\n### Basic Analysis\n\n```\nShow me correlations in the sales dataset\nCreate a bar chart of sales by region\nAnalyze the distribution of revenue column\n```\n\n### Advanced Analytics\n\n```\nValidate data quality for sales dataset\nCompare sales dataset with marketing dataset\nGenerate dashboard with revenue trends and regional breakdown\n```\n## 🔧 Available Tools\n\n### Dataset Management\n- `load_dataset` - Load CSV/JSON files with automatic schema discovery\n- `list_loaded_datasets` - View all datasets in memory\n- `get_dataset_info` - Get detailed dataset information\n- `clear_dataset` / `clear_all_datasets` - Memory management\n\n### Core Analytics\n- `segment_by_column` - Analyze categorical data segments\n- `find_correlations` - Discover relationships between variables\n- `analyze_distributions` - Statistical distribution analysis\n- `detect_outliers` - Identify data anomalies\n- `suggest_analysis` - AI-powered analysis recommendations\n\n### Visualization\n- `create_chart` - Generate interactive charts (bar, scatter, line, histogram)\n- `generate_dashboard` - Multi-chart dashboards\n\n### Advanced Analytics\n- `validate_data_quality` - Comprehensive data quality scoring\n- `compare_datasets` - Multi-dataset comparison analysis\n- `merge_datasets` - Join datasets with flexible strategies\n- `calculate_feature_importance` - ML feature importance analysis\n- `export_insights` - Export results in multiple formats\n\n## 📂 Supported File Formats\n\n### CSV Files\n- Standard CSV with headers\n- Custom delimiters automatically detected\n- UTF-8 encoding support\n- Large file handling with sampling options\n\n### JSON Files\n- Flat JSON structures\n- Nested JSON (automatically flattened)\n- JSON Lines format\n- Array of objects format\n\n## 🛠️ Configuration\n\n### Manual Configuration\n\nIf the automatic setup doesn't work, manually edit your Claude Desktop config:\n\n**Location:** `%APPDATA%\\Claude\\claude_desktop_config.json`\n\n```json\n{\n  \"mcpServers\": {\n    \"quick-data-windows\": {\n      \"command\": \"python\",\n      \"args\": [\n        \"C:\\\\path\\\\to\\\\your\\\\quick-data-for-windows-mcp\\\\main.py\"\n      ],\n      \"cwd\": \"C:\\\\path\\\\to\\\\your\\\\quick-data-for-windows-mcp\",\n      \"env\": {\n        \"LOG_LEVEL\": \"INFO\",\n        \"PYTHONPATH\": \"C:\\\\path\\\\to\\\\your\\\\quick-data-for-windows-mcp\\\\src\"\n      }\n    }\n  }\n}\n```\n\n### Alternative: Using UV Package Manager\n\nIf you prefer UV (recommended for Python dependency management):\n\n```json\n{\n  \"mcpServers\": {\n    \"quick-data-windows\": {\n      \"command\": \"uv\",\n      \"args\": [\n        \"--directory\",\n        \"C:\\\\path\\\\to\\\\your\\\\quick-data-for-windows-mcp\",\n        \"run\",\n        \"python\",\n        \"main.py\"\n      ]\n    }\n  }\n}\n```\n\n## 🧪 Testing the Server\n\nTest the server standalone (before Claude Desktop integration):\n\n```bash\npython main.py\n```\n\nExpected output:\n```\nQuick Data for Windows MCP v1.0.0\nServer running on stdio...\n```\n\n## 📊 Example Workflows\n\n### Sales Data Analysis\n```\n1. Load sales_data.csv as \"sales\"\n2. Show correlations in sales dataset\n3. Create bar chart of sales by product_category \n4. Detect outliers in revenue column\n5. Generate dashboard with top products and regional trends\n```\n\n### Data Quality Assessment\n```\n1. Load customer_data.csv as \"customers\"\n2. Validate data quality for customers dataset\n3. Analyze distributions for age column\n4. Segment by customer_type column\n```\n\n## 🔍 Troubleshooting\n\n### Common Issues\n\n**\"Module not found\" errors:**\n- Ensure Python is in your PATH\n- Run `pip install -r requirements.txt` manually\n- Check that PYTHONPATH is set correctly in config\n\n**\"File not found\" errors:**\n- Use full Windows paths: `C:\\Users\\...`\n- Avoid relative paths like `.\\data\\file.csv`\n- Check file permissions\n\n**Claude Desktop not finding server:**\n- Restart Claude Desktop after config changes\n- Check config file syntax with JSON validator\n- Verify file paths are correct (no typos)\n\n### Getting Help\n\n1. Check that Python 3.9+ is installed: `python --version`\n2. Verify dependencies: `pip list | findstr pandas`\n3. Test server manually: `python main.py`\n4. Check Claude Desktop logs for errors\n\n## 🤝 Contributing\n\nThis is a community-driven Windows adaptation of the original quick-data-mcp project. Contributions welcome!\n\n### Development Setup\n```bash\n# Clone and setup\ngit clone https://github.com/Beaulewis1977/quick-data-for-windows-mcp.git\ncd quick-data-for-windows-mcp\n\n# Install development dependencies\npip install -r requirements.txt\npip install pytest black ruff\n\n# Run tests (when implemented)\npytest tests/\n```\n\n## 📝 License\n\nMIT License - see LICENSE file for details.\n\n## 🙏 Acknowledgments\n\n**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).**\n\n### Original Project Credits\n- **Original Author:** [@disler](https://github.com/disler)\n- **Original Repository:** [disler/quick-data-mcp](https://github.com/disler/quick-data-mcp)\n- **Original Purpose:** MCP server for data analytics with Claude Code\n- **License:** MIT (maintained in this fork)\n\n### Windows Fork Contributions\n- **Windows Compatibility:** [@Beaulewis1977](https://github.com/Beaulewis1977)\n- **Claude Desktop Integration:** Community-driven improvements\n- **Troubleshooting \u0026 Documentation:** Enhanced for Windows users\n\n### Technology Stack\n- **Model Context Protocol:** [Anthropic](https://anthropic.com)\n- **Data Processing:** pandas, numpy, plotly, scikit-learn\n- **Platform:** Optimized for Windows + Claude Desktop\n\n**⭐ Please star both repositories:**\n- [Original Project](https://github.com/disler/quick-data-mcp) - For the core innovation\n- [This Fork](https://github.com/Beaulewis1977/quick-data-for-windows-mcp) - For Windows support\n\nSpecial thanks to [@disler](https://github.com/disler) for creating the foundational work that made this Windows adaptation possible!\n\n## 🔗 Links\n\n- [Claude Desktop](https://claude.ai/desktop)\n- [Model Context Protocol](https://modelcontextprotocol.io/)\n- [Original Quick Data MCP](https://github.com/disler/quick-data-mcp)\n- [Python for Windows](https://www.python.org/downloads/windows/)\n\n---\n**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.\n\n**Ready to analyze your data with AI? Load a CSV and start exploring! 🚀**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbeaulewis1977%2Fquick-data-for-windows-mcp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbeaulewis1977%2Fquick-data-for-windows-mcp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbeaulewis1977%2Fquick-data-for-windows-mcp/lists"}