Excel Vision MCP server

📊 Excel Vision MCP

Your AI reads the spreadsheet. It can't see the diagram in cell B12.

This fixes that. Other Excel MCP servers return cell values and silently drop every embedded image, so the flowchart your spec depends on never reaches the model. Excel Vision MCP returns them as native ImageContent your AI can actually look at — alongside the text, formatting, and formulas.

Installation · Tools · Configuration · How It Works · FAQ

🤔 The Problem

Ask your assistant to review a requirements spec. Half the meaning lives in screenshots, flowcharts, and annotated diagrams pasted into cells — and every Excel MCP server hands the model text only. The answer comes back confident and incomplete, because the model never knew the pictures existed.

The same blind spot applies to the other signals authors leave behind:

Same file. One agent sees a table of strings; the other sees what the author actually meant.

✨ Key Features

Image Extraction — What Makes This Different

Most Excel MCP servers only read cell values. This server uses a dual extraction strategy:

1. Cell-Position Mapping (primary) — Maps each image to its exact cell location using openpyxl-image-loader
2. Archive Scanning (fallback) — Scans the xlsx ZIP archive's xl/media/ directory to catch any images missed by method 1

The result: zero images left behind, with position metadata when available.

👀 See It In Action

A requirements spec where the workflow lives in a pasted diagram and the status lives in cell colors:

You: Review this spec and tell me which features are still in scope, and how the dispatch flow works.

readfullcontent returns the sheet as text with formatting markers, then the embedded diagram as an image:

Shortened. The full README is on GitHub.