MCP Excel Reader

Created By
ArchimedesCryptoa year ago
A Model Context Protocol (MCP) server for reading Excel files with automatic chunking and pagination support. Built with SheetJS and TypeScript.
Overview

What is MCP Excel Reader?

MCP Excel Reader is a Model Context Protocol (MCP) server designed for reading Excel files efficiently, featuring automatic chunking and pagination support. It is built using SheetJS and TypeScript, making it ideal for handling large datasets.

How to use MCP Excel Reader?

To use MCP Excel Reader, you can install it via Smithery or as an MCP server. After installation, you can read Excel files by invoking the read_excel tool with the required parameters such as file path and optional sheet name.

Key features of MCP Excel Reader?

  • 📊 Supports reading Excel files (.xlsx, .xls) with automatic size limits.
  • 🔄 Automatic chunking for large datasets to manage memory efficiently.
  • 📑 Allows sheet selection and row pagination for targeted data extraction.
  • 📅 Proper handling of date formats.
  • ⚡ Optimized for performance with large files.
  • 🛡️ Includes error handling and validation for robust operation.

Use cases of MCP Excel Reader?

  1. Efficiently reading large Excel files in data analysis applications.
  2. Extracting specific sheets or rows from complex Excel documents.
  3. Integrating with AI systems for automated data processing tasks.

FAQ from MCP Excel Reader?

  • Can MCP Excel Reader handle very large Excel files?

Yes! It is designed to automatically chunk large files into manageable sizes for efficient processing.

  • Is there a limit to the number of sheets I can read?

No, you can read as many sheets as your Excel file contains, with the option to specify which one to read.

  • How do I install MCP Excel Reader?

You can install it via Smithery or by cloning the repository and following the installation instructions provided in the documentation.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
ArchimedesCrypto
Star
-
Language
-
License
-

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago
Crevio

2 days ago