"How to Read and Write Excel Files" matching MCP servers:

A Model Context Protocol server that enables AI assistants to read from and write to Microsoft Excel files, supporting formats like xlsx, xlsm, xltx, and xltm.

Enables reading and writing Excel files (text, formulas, and images on Windows) via MCP tools with pagination support.

Enables reading and writing of values, formulas, and formatting in Microsoft Excel files including .xlsx and .xlsm formats. It supports sheet management, table creation, and provides Windows-exclusive features like live editing and screen capture.

Enables reading and writing MS Excel data, including values, formulas, sheets, tables, and cell formatting, with optional screen capture on Windows.

Enables reading and writing MS Excel files, including cell values, formulas, sheet creation, copying, formatting, and on Windows, live editing and screen captures.

CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.

MCP server that enables AI assistants to drive systematic literature review workflows, including screening, downloading, converting, and reviewing papers through natural language conversation.

An MCP server that gives AI agents structured read/write access to a story-based project backlog. Agents can list stories, read content, update status, and append notes — all backed by plain markdown files that live inside your project repository. There is no shared server. The backlog files live in your repo under requirements/, committed and versioned alongside your code

MCP server for managing interactive processes, enabling AI agents to start, interact with, and terminate long-running programs like SSH sessions, REPLs, and installers via read/write operations.

Read-only MCP tools for authenticated Open Science Framework projects, components, files, and contributors.

Figma MCP server with full read/write access via plugin bridge — no API token, no rate limits. 58 tools for design automation: styles, variables, components, prototypes, and content.

Talk to AWS CLI from an MCP-speaking agent. Run any aws <service> <operation> command through the Model Context Protocol, with read-only defaults and gated write access.

Provides git-aware safe file operations, allowing AI agents to delete files while protecting git-tracked source code from accidental deletion.

High-performance MCP data plane server for Nextcloud integration, enabling AI agents to read, write, organize, and manage files and CRM assets over WebDAV and OCS APIs.

A single static Go binary that exposes GitHub operations (repos, branches, commits, file contents, issues, PRs, and search) as MCP tools, enabling agents to read and write GitHub data with no runtime dependencies.

Enables finding files and knowing their location and permissions, organizing folders, moving and copying content, transferring files in and out, managing sharing with transparency, tracking changes, and handling shared drives.

A local MCP server that unifies email and calendar management across multiple providers, enabling AI agents to search, read, and write with explicit approval and local-first security.

Enables local macOS integration between Apple Reminders and Home Assistant via an MCP server, using EventKit to read and write allowlisted data.

An MCP server for TrueNAS SCALE that enables read-first management of storage, system, sharing, and virtualization resources with per-user API key authentication, and optional write operations.

LLM Optimizer is an AI visibility intelligence platform. It analyzes how large language models and AI search engines perceive, cite, and recommend brands; then provides research-backed optimization strategies to improve that visibility.