"excel" matching MCP servers:

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

Reads Excel files and returns each sheet's content as CSV text. Enables AI models to extract data from Excel spreadsheets via natural language.

Enables AI agents to read Excel files with full content extraction, including embedded images, cell data, formulas, and merged cells, returning multimodal content for vision-capable models.

MCP server for reading and inspecting local Excel files (.xlsx, .xlsm, .xls, .xlsb, .ods) with tools for inspecting metadata, reading ranges, and profiling structure.

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 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.

Enables AI models to search, read, and analyze Excel files from your local file system with support for multiple worksheets, text search, and JSON data conversion.

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.

Enables efficient reading, analyzing, and querying of Excel, CSV, and JSON files with support for chunked processing, column/field filtering, and streaming for large datasets. Supports multiple transport protocols (stdio, HTTP, SSE) for flexible integration.

Enables MCP clients to upload tabular datasets and run deterministic Pandas, NumPy, Excel/openpyxl, and automated EDA operations through registered tools.

Enables read-only SQL querying and exploration of data files (CSV, Parquet, JSON, Excel, etc.) via DuckDB, supporting local paths, globs, URLs, and S3 buckets.

MCP server that profiles local data files (CSV, Parquet, JSON, Excel) and returns compact structured summaries with data-quality flags, enabling AI agents to understand datasets without seeing raw rows.

Enables LLMs to profile and analyze tabular data files (CSV, Parquet, Excel, JSON) by extracting schema, statistics, data quality issues, and dtype suggestions, returning structured JSON.

Enables creating and deploying KoboToolbox XLSForm questionnaires, managing data collection, analyzing submissions, and generating Excel, Word, and PDF deliverables directly from a Claude conversation.

Parses various document formats (PDF, Word, Excel, PowerPoint) into Markdown content using NiuTrans API, enabling extraction and reading of document text through natural language interactions.

A lightweight document parser MCP server that enables Claude to parse PDFs, Word, Excel, images (OCR), and other document formats with support for chunking and metadata extraction.

Enables LLMs to access, analyze, and extract information from STDF-V4 semiconductor test data files, supporting metadata extraction, parametric analysis, yield calculations, and multi-site test data filtering with CSV/Excel export capabilities.

Enables AI assistants and editors to profile, clean, and analyze messy CSV/Excel files directly through MCP tools such as profile_dataset, clean_dataset, and list_sheets.

Enables LLM agents to load, explore, and analyze CSV and Excel files using DuckDB, with tools for SQL querying, statistical analysis, expense optimization, and anomaly detection.

Enables AI assistants to perform statistical analysis on MySQL databases, generating formatted Excel reports with t-tests and effect sizes, and creating thesis-quality Word documents with AI-powered insights.