"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.

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.

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.

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 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 agents to read messy lab and instrument spreadsheet exports by detecting headers, cleaning table bounds, parsing decimal commas, preserving LOD/LOQ qualifiers, and returning JSON rows with column metadata.

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

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.

Provides secure, agentic Excel analysis and calculation capabilities, enabling users to inspect workbook structure, perform statistical computations, write formulas, and generate outputs through whitelisted MCP tools with audit trails and backups.

Enables MCP clients to load CSV, Excel, and other tabular files, profile datasets, and answer questions by executing LLM-written pandas code in a sandboxed subprocess.

Enables discovery of official DHS country, survey, and indicator metadata; retrieval of public aggregate estimates; assessment of comparison risks; and export of auditable CSV, JSON, Excel, or executable notebook bundles.

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.

An MCP server that exposes the local GEMPACK CGE toolchain (TABLO, GEMSIM, HAR utilities) as tools Claude can call: compile models, run simulations, read solution and HAR data files, and export to CSV/Excel.

Enables data analysis and visualization operations such as loading CSV/Excel/JSON files, computing summary statistics, generating charts, and exploring datasets via SSE/HTTP.

Enables AI to efficiently analyze and extract structured data from complex documents, especially Excel files, by providing tools like section reading and field mapping to reduce token usage and improve success rates.

Provides three MCP servers for interacting with Excel files, PDF documents, and SQLite databases, enabling AI assistants to read, create, update, and analyze local resources.

MCP server for analyzing building sustainability metrics via Excel, PDF, and frameworks like ESG, LEED, BREEAM, DGNB with IFC integration.

Read and filter Excel, CSV, ODS, SQLite, Parquet and MTSV files — or a folder — as plain text

Universal MCP server for extracting text from various document formats including PDF, Excel, Word, CSV, and more, with support for streaming, limits, and markdown conversion.

Enables comprehensive content analysis through web scraping, document processing (PDF, DOCX, TXT, RTF), screenshot analysis, and local Excel database management. Provides intelligent workflows for extracting, analyzing, and storing content from multiple sources with automated categorization and search capabilities.

MCP server that enables intelligent analysis of legal spend data across multiple sources (LegalTracker, databases, CSV/Excel files), providing features like spend summaries, vendor performance analysis, and budget comparisons.

Enables LLMs to search, preview, and query data assets from ICRISAT's federation-first data hub, supporting CSV, Excel, and Word files with SQL access via DuckDB.

Enables interactive data analysis using a real IPython kernel with session management, supporting CSV/Excel/JSON loading, code execution, and variable monitoring.

Enables analysis of datasets from CSV/Excel files, Google Sheets, and Google Drive with comprehensive data profiling tools including schema inference, missing value reports, correlation analysis, and outlier detection. Supports exporting analytical reports in multiple formats to local storage or Google Drive.

An AI-driven tool for processing survey data that supports cross-tabulation, NPS and satisfaction scoring, and automated Excel report generation. It enables users to analyze datasets via natural language for tasks like merging response options and identifying demographic differences.

Analyze survey data (.sav, .csv, .xlsx) through Claude — crosstabs with significance testing, ANOVA, correlation, gap analysis, and publication-ready Excel exports. Upload once, analyze unlimited.

Provides intelligent construction quotation and cost lookup for Colombia, enabling natural language queries for activities, categories, and detailed pricing from an Excel database.

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.