"A guide for data cleaning and analysis in Excel" matching MCP servers:

Provides comprehensive statistical analysis tools for industrial data including time series analysis, correlation calculations, stationarity tests, outlier detection, causal analysis, and forecasting capabilities. Enables data quality assessment and statistical modeling through a FastAPI-based MCP architecture.

An MCP server for data analysis and visualization supporting CSV and Excel files. It enables users to generate statistical summaries and create multi-dimensional charts like heatmaps and bar plots through natural language.

An MCP server that answers natural-language questions over CSV, Excel, and SQL data by providing deterministic tools for loading, profiling, querying, cleaning, statistical analysis, visualization, and reporting. It enables LLMs to plan and interpret while all computation is done exactly through MCP tools.

Enables users to preprocess, analyze, and visualize CSV data through comprehensive tools for data manipulation, statistical analysis, and graph generation.

Enables AI clients to read, write, and manage Excel workbooks (.xlsx/.xlsm) directly via openpyxl, with comprehensive tools for data, formatting, formulas, charts, and more.

Enables AI agents to analyze Excel files through atomic operations like filtering, aggregation, and grouping without loading raw data into context.

Enables normalizing arbitrary Excel spreadsheets with varied headers into 19 canonical fields and clean JSON, with optional LLM disambiguation and offline fallback. Exposes MCP tools for use in Claude, Cursor, and Windsurf.

Enables querying Excel and CSV files using SQL via natural language, allowing AI assistants to analyze data without manual SQL writing.

An MCP server that allows LLMs to read, analyze, and interact with Excel files through file operations, data discovery, and comprehensive analysis tools.

Generates formatted Excel (.xlsx) files from user requests and deposits them into Cleyrop project data.

A Model Context Protocol server that enables AI assistants to read from and write to Microsoft Excel files, supporting formats like xlsx, xlsm, xltx, and xltm.

An MCP server that provides comprehensive Excel file operations, data analysis, and visualization capabilities for working with various spreadsheet formats like XLSX, CSV, and JSON.

Enables LLMs to work with Excel and CSV files through structured tools for workbook operations, formatting, charts, ETL, analysis, and more.

Enables users to analyze local Excel and CSV files through natural language queries and a web dashboard while keeping data local. It supports saving specific analyses as reusable tools and building a custom analytics toolkit within Claude Desktop.

A Model Context Protocol (MCP) server that provides tools for reading Excel (xlsx) files, enabling extraction of data from entire workbooks or specific sheets with results returned in structured JSON format.

Enables conversational data analysis of Excel/CSV files through natural language queries, powered by 395 Excel functions via HyperFormula and multi-provider AI. Supports advanced analytics, bulk operations, financial modeling, and large file processing with intelligent chunking.

An MCP server for reading, writing, and analyzing Excel files using Python, pandas, and openpyxl. It enables tasks such as managing multiple worksheets, performing structural data analysis, and creating new files from JSON data.

Enables AI agents to read real Excel files with messy layouts, auto-detecting header rows and handling merged cells to extract clean tabular data via MCP tools.

A Windows-optimized server providing universal data analytics for JSON and CSV files through over 32 tools including schema discovery and interactive visualizations. It is specifically designed for seamless integration with Claude Desktop on Windows.

Enables AI agents to operate Excel files through standardized MCP interfaces, including merging, splitting by column, and exporting multi-sheet workbooks.