Agent-Native Calendar
Agent-Native Google Calendar - manage events, sync, and public booking
Description from the maker (original English)
Read real, messy Excel files from an agent: multiple sheets, title rows, merged cells.
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Pick the AI app you use, then copy the settings.
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"excel": {
"command": "uvx",
"args": [
"excel-agent-mcp"
]
}
}
}Run this in your terminal
claude mcp add excel -- uvx excel-agent-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"excel": {
"command": "uvx",
"args": [
"excel-agent-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"excel": {
"type": "stdio",
"command": "uvx",
"args": [
"excel-agent-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account wesseltl, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.2) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Agent-Native Calendar, Excel MCP Server, MCP Server for Excel
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Agent-Native Google Calendar - manage events, sync, and public booking
Lets AI create and edit Excel files itself, including formulas, charts and PivotTables, without Excel installed.
Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Let your AI agent read real, messy Excel files. An MCP server that handles the things LLMs choke on: multiple sheets, title rows sitting above the actual table, and merged cells.
If you paste a spreadsheet into a prompt, the model has to guess where the data starts and what the merged cells mean, and it often gets it wrong. This reads the file properly with deterministic code, so the values are exact and the model never invents cell contents.
A real spreadsheet almost never starts cleanly at cell A1:
A1: Quarterly Sales Report 2024 <- title, not data
A2: Generated by finance <- note, not data A3: (blank) A4: Region | Product | Units <- the actual header A5: North | Widget | 120 ...
Ask an LLM to read that and it'll often treat the title as a column. read_table auto-detects that the header is on row 4 and returns clean records. Merged cells (a value spanning several rows) get forward-filled, so rows don't lose their category.
| Tool | What it does |
|---|---|
list_sheets(path) | Every sheet in the workbook, with its size |
preview_sheet(path, sheet, rows) | Top rows as a grid, so the agent can see the layout |
read_table(path, sheet) | The actual data table as records. Reports the decisions that could be wrong: header_source (explicit / auto-detected), header_confidence, and forward_filled_columns (values inferred from merged cells, not read) |
sheet_to_csv(path, sheet) | The table as clean CSV text |
The fastest way to use this is with an MCP client like Claude Desktop. Three steps:
1. Install it
pip install "excel-agent-mcp[mcp]"
2. Add it to your client's config
Claude Desktop's config lives here:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonAdd the server:
{
"mcpServers": { "excel": { "command": "excel-agent-mcp" } } }
3. Restart Claude Desktop. You'll see a tools icon appear, meaning the server is connected.
That's it. Now ask about any .xlsx file on your machine:
You: What's in /Users/me/reports/sales.xlsx?
Agent (calls list_sheets, then read_table): The workbook has one sheet, "Q1". The table starts on row 4 (the rows above are a title). 3 rows: North/Widget/2400, South/Widget/3000, South/Gadget/2400. Total revenue 7800.
The agent reads the real file instead of guessing, so the numbers are exact.
Restricting file access: to stop the agent reading anything outside one folder, set
EXCEL_MCP_ALLOWED_DIR. See SECURITY.md.
The same server works in any MCP client, only the config differs. Use excel-agent-mcp as the command.
Cursor — ~/.cursor/mcp.json (global) or .cursor/mcp.json (per project). Same shape as Claude Desktop, and it hot-reloads (no restart):
{ "mcpServers": { "excel": { "command": "excel-agent-mcp" } } }
VS Code / GitHub Copilot — .vscode/mcp.json. Note the different key (servers, not mcpServers) and the required type. Tools only run in Copilot Agent mode:
{ "servers": { "excel": { "type": "stdio", "command": "excel-agent-mcp" } } }
Windsurf — ~/.codeium/windsurf/mcp_config.json (create it if missing). Same shape as Claude Desktop:
{ "mcpServers": { "excel": { "command": "excel-agent-mcp" } } }
Cline — add it from the extension's MCP settings panel in VS Code (command: excel-agent-mcp).
read_table doesn't just return the data, it tells you how confident it is, so you can trust a clean parse and double-check a guess:
{
"columns": ["Region", "Product", "Revenue"], "rows": [ ... ], "header_row": 3, "header_source": "auto-detected", "header_confidence": 0.42, "forward_filled_columns": ["Region"] }
"explicit" if you told it which row is the header, "auto-detected" if it guessed.0..1 for an auto-detected header. A low value means it was a close call; if the result looks off, pass an explicit header_row.The idea: surface the decisions that could be wrong, instead of handing back tidy-looking output that hides a guess.
from excel_mcp import reader
reader.list_sheets("report.xlsx") reader.read_table("report.xlsx", "Sales") # {'columns': [...], 'header_source': ..., ...} reader.sheet_to_csv("report.xlsx", "Sales")
python -m unittest discover -s tests # builds its own messy xlsx, runs anywhere
MIT