mcp-csv-database

# MCP CSV Database Server A Model Context Protocol (MCP) server that provides comprehensive tools for loading CSV files into a temporary SQLite database and performing advanced data analysis with AI assistance. ## Features - **Smart CSV Loading**: Automatically detect CSV separators and load multiple files from a folder - **Advanced SQL Queries**: Execute any SQL query with automatic result formatting and pagination - **Schema Inspection**: View database schema, table structures, and relationships - **Data Quality Analysis**: Comprehensive missing data analysis, duplicate detection, and data profiling - **Statistical Analysis**: Column statistics, data summaries, and distribution analysis - **Export Capabilities**: Export query results or tables back to CSV with custom formatting - **Performance Tools**: Create indexes, analyze query execution plans, and optimize performance - **AI-Ready**: Designed for seamless integration with AI assistants for data analysis workflows ## Installation ### From PyPI ```bash pip install mcp-csv-database ``` ### From source ```bash git clone https://github.com/Lasitha-Jayawardana/mcp-csv-database.git cd mcp-csv-database pip install -e . ``` ## Usage ### Command Line Start the server with stdio transport: ```bash mcp-csv-database ``` **Recommended**: Auto-load CSV files from a folder using positional argument: ```bash mcp-csv-database /path/to/csv/files ``` Alternative syntax with explicit flag: ```bash mcp-csv-database --csv-folder /path/to/csv/files ``` With custom table prefix: ```bash mcp-csv-database /path/to/csv/files --table-prefix sales_ ``` For remote access with HTTP transport: ```bash mcp-csv-database /path/to/csv/files --transport sse --port 8080 ``` ### Configuration Add to your MCP client configuration: ```json { "mcpServers": { "csv-database": { "command": "mcp-csv-database", "args": ["/path/to/your/csv/files"] } } } ``` Alternative configuration with explicit options: ``…