"Reading and Writing Word Files" matching MCP servers:

An MCP server that provides tools for reading, writing, and editing files on the local filesystem.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

Provides AI coding agents a full abap2UI5 development loop—writing ABAP classes, validating views, deploying, and running apps headless with screenshots—all locally without an SAP system.

Connects AI agents to microsandbox for creating lightweight sandboxes, executing code, managing files, and monitoring resources.

An MCP server that lets AI coding agents work on Godot 4 projects, including reading and editing scenes, writing and validating GDScript, running the game, and capturing screenshots.

A comprehensive MCP server providing tools for AI agents to interact with code, including reading symbols, importing modules, replacing text, and sending OS notifications.

Enables programmatic interaction with Jupyter notebooks, allowing reading, editing, and executing cells via Claude.

MCP server that delegates code writing, editing, and execution to OpenCode, allowing AI assistants to focus on decision-making.

An MCP server that gives an agent terminal and file-management capabilities, including running shell/Python commands, searching and reading files, and creating/editing/deleting files and folders.

A demonstration server implementing the Model Context Protocol (MCP) with both STDIO and Server-Sent Events (SSE) support, featuring a word reversal tool that transforms input text by reversing characters.

A minimal reference implementation of an MCP server that responds with "Hello, World" via Streamable HTTP. Serves as a baseline for integration testing and MCP client development with production-ready features including health checks, metrics, and containerized deployment.

A Model Context Protocol server that enables LLMs to read, search, and analyze code files with advanced caching and real-time file watching capabilities.

A Model Context Protocol server that provides programmatic access to the Windows terminal, enabling AI models to interact with the Windows command line through standardized tools for writing commands, reading output, and sending control signals.

A comprehensive TypeScript boilerplate MCP server featuring domain-driven design and dynamic component loading. Provides example tools for calculations and text processing, system resources, and writing assistance prompts.

Enables inspection and editing of Jupyter notebook files (.ipynb) through tools for reading, adding, updating, deleting, moving, and converting cells while preserving metadata.

Enables running multiple Claude prompts simultaneously in parallel with support for file contexts and output redirection to individual files.

A Model Context Protocol server that enables AI assistants to securely interact with OceanBase databases by listing tables, reading data, and executing SQL queries through a controlled interface.

A Python-based text editor server built with FastMCP that provides tools for file operations. This server enables reading, editing, and managing text files through a standardized API following a multi-step process.

A minimal Model Context Protocol server in TypeScript that demonstrates MCP-compliant resources and tools for LLMs, featuring simple resources and a basic tool that echoes messages or returns greetings.

Enables AI agents to interact with the Roark API by writing and executing TypeScript SDK code in an isolated sandbox, with built-in documentation search to guide those tasks.