MCP Text Editor Server

📋 Overview:

This webpage is the GitHub repository for a project named "mcp-text-editor" by user tumf. It is a Model Context Protocol (MCP) server designed to facilitate line-based text file operations, optimized for Language Learning Model (LLM) tools with efficient partial file access to minimize token usage. The repository is public and users are able to browse the source code, view issues, pull requests, and contribute to the project.

⭐ Key Points:

• The project provides a Model Context Protocol (MCP) server for line-oriented text file editing.


• It is optimized for LLM tools, focusing on efficient partial file access and minimizing token usage.


• The project features safe concurrent editing with hash-based validation.


• It provides atomic multi-file operations and robust error handling.


• The text editor has character encoding support, including UTF-8, Shift_JIS, and Latin1.


🔍 Main Findings:

• The project implements two primary tools: `gettextfilecontents` (for retrieving file content with range specification) and `patchtextfilecontents` (for applying changes with conflict detection).


• The server is set up to prevent directory traversal attacks and ensures sanitized user inputs.


• The code uses Python type hints and is formatted with Black and Ruff.


• The test coverage for the project is reported to be 90%.


• The repository contains 11 items including workflow, source, test, and configuration files.


📊 Details:

• Installation: Requires Python 3.11+ and a POSIX-compliant OS or Windows. Installation through `uvx` and `smithery` is recommended.


• Configuration: Includes configuration instructions for Claude.app users.


• Contributing: Outlines the steps for contributing, including forking the repository, creating feature branches, running tests, and submitting pull requests.


• Structure: Includes the main Python implementation files, tests, and configuration.

🎯 Conclusion:
The "mcp-text-editor" repository hosts a Model Context Protocol server for text file editing, emphasizing efficiency and safety for LLM tools. The project is open for contributions and provides detailed documentation for setup, usage, and troubleshooting.