"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.

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

A workshop repository teaching advanced Model Context Protocol features for building AI-connected apps with deeper integration capabilities.

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

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

A Model Context Protocol server that enables Claude to execute Python code using boto3 to query and manage AWS resources directly from conversations.

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 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.

Provides Excel file manipulation capabilities without requiring Microsoft Excel installation, enabling workbook creation, data manipulation, formatting, and advanced Excel features.

Enables AI agents to create, read, and modify Excel workbooks without requiring Microsoft Excel, supporting operations like formulas, charts, pivot tables, formatting, and data validation.

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

Provides full read and write access to Excel workbooks (sheets, cell ranges, tables, formulas, formatting, and cross-workbook references) via MCP, running locally or as an HTTP/SSE service.

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

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

Enables AI agents to read and query Excel files stored in SharePoint and OneDrive for Business, converting permission-matrix spreadsheets into structured JSON for automated QA workflows.