# mcp-excel

> Use this tool when you need to analyze Excel files without loading large datasets into memory. It solves problems like data filtering, aggregation, and grouping, enabling efficient data processing through atomic operations. The mcp-excel tool accepts Excel files as input and outputs filtered, aggregated, or grouped data, making it ideal for use cases requiring data insights from spreadsheet files.

Canonical page: https://skillsregistry.net/skills/jwadow-mcp-excel  
JSON: https://api.skillsregistry.net/v1/skills/jwadow-mcp-excel

## Description

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

## Trust

- **Trust score (0–1):** 0.52
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/nxn4bn6y0e)
- **Repository:** <https://github.com/jwadow/mcp-excel>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "jwadow-mcp-excel"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jwadow-mcp-excel` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jwadow-mcp-excel/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt