sbroenne/mcp-server-excel

Automate real Microsoft Excel with AI via MCP Server or CLI — Power Query, DAX, VBA, PivotTables, charts, and 412 operations.

What it solves

ExcelMcp allows AI agents (such as Claude, ChatGPT, and GitHub Copilot) to control the actual Microsoft Excel application on Windows. Unlike tools that simply parse files, this project provides a bridge for AI to perform complex operations like refreshing Power Query, running VBA/Python scripts, and managing PivotTables and charts directly within the live application.

How it works

The project implements the Model Context Protocol (MCP), allowing AI assistants to discover and expose 31 tools with 387 operations. It interacts with Excel via the official COM API, meaning the AI can drive the real Excel software. It offers two interfaces: an MCP Server for conversational assistants and a CLI for scripts and coding agents to reduce token usage.

Who it’s for

Windows users who want to automate their Excel workflows using natural language, specifically those who use advanced features like DAX, Power Pivot, and the Data Model.

Highlights

  • Live Application Control: Drives the real Excel app rather than editing files on disk.
  • Comprehensive Toolset: Provides 387 operations covering data analytics, cells, workbooks, and visuals.
  • Advanced Excel Support: Supports Power Query, DAX, VBA, and Python in Excel (=PY()).
  • Flexible Interfaces: Available as an MCP server for LLM clients or a CLI for automation scripts.

Related

  • Project
    haris-musa/excel-mcp-server

    An MCP server that enables AI clients to create, read, and edit Excel files, including charts and PivotTables, without needing Microsoft Excel installed.

  • Project
    microsoft/powerbi-modeling-mcp

    An MCP server that enables AI agents to build and modify Power BI semantic models using natural language, supporting bulk operations and DAX validation.

  • Project
    tmustier/pi-for-excel

    Pi for Excel is an open‑source Office add‑in that embeds a conversational AI agent inside Microsoft Excel. The agent can read, write, format, and analyse spreadsheets using any LLM you configure, offering 16 built‑in spreadsheet tools, session management, automatic checkpoints for one‑click rollback, and extensible sandboxed extensions.

  • Project
    dbt-labs/dbt-mcp

    dbt‑MCP Server is an open‑source service that exposes a large catalog of dbt‑related tools (SQL execution, semantic‑layer queries, model discovery, dbt CLI commands, job administration, code generation, and documentation lookup) via the Model Context Protocol. It lets LLM‑powered agents understand and act on a dbt project—generating SQL from natural language, running dbt jobs, fetching lineage, and even creating new model files—making it a concrete bridge between data‑engineering metadata and AI assistants.

  • Project
    daobataotie/CAD-MCP

    CAD‑MCP is a Windows‑only Python server that exposes AutoCAD/GstarCAD/ZWCAD functionality through the Model‑Context‑Protocol. It lets LLM‑powered clients control drawing, querying, editing, layer, block, and file operations via 35 structured JSON tools, enabling natural‑language‑driven CAD automation.