"Exploring Excel: Tools, Features, and Resources" matching MCP servers:

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.

Provides Dev Container Features that install code intelligence (LSP) and repository knowledge search (Orama) MCP servers into any dev container, enabling coding agents to perform go-to-definition, find references, and hybrid search over project files.

Web scraper and token compressor that converts HTML to clean markdown with 70-80% fewer tokens. Single-page compression and multi-page BFS crawling with auto-fallback fetch modes.

Enables AI assistants to read and write local Excel and CSV files, supporting editing, styling, and image insertion.

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.

MCP server that demonstrates the Resources feature by exposing static and dynamic resources, including contact data and personalized greetings, through MCP.

Enables local Excel workbooks to be read, modified, recalculated, and verified with screenshots through a single operation pipeline, automatically choosing openpyxl or Excel COM.

An MCP server for performing Excel file operations including read, write, and manipulation, with enterprise security features and VS Code integration.

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

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

Enables AI assistants to read, write, and manipulate Excel files through comprehensive spreadsheet operations. Supports file management, data querying, worksheet operations, formula calculations, and includes security features like path validation and automatic backups.

Enables MCP clients to create and manipulate Excel workbooks programmatically, including sheets, cell data, formatting, formulas, charts, and pivot tables.

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.

Enables AI assistants to perform comprehensive Microsoft Excel operations including data analysis, cell editing, advanced formatting, and VBA execution on Windows systems. It provides a structured workflow for managing workbooks and worksheets through a dedicated Model Context Protocol interface.

Attaches to already-open Excel workbooks on Windows via COM to enable live editing of cells, ranges, formatting, and comments, without launching or closing Excel itself.

Live Excel MCP server for macOS that interacts with running Excel instances in real time via AppleScript, enabling instant read/write, formula support, and VBA macro execution.

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 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.

Provides efficient handling of large Excel files through automatic chunking and pagination, using MCP to enable seamless file reading and management features such as sheet selection and error handling.

Enables AI assistants to read, write, format, and analyze Excel files with 34 tools, including real-time editing on macOS with Microsoft Excel.