"A simple MCP server or implementation" matching MCP servers:

A modular MCP server that provides comprehensive system automation capabilities including file operations, Telegram integration, job scheduling, system control, and YouTube downloads. Features persistent data storage and a clean architecture for easy extension and maintenance.

Enables Copilot to safely read one explicitly selected source file from a configured root directory via a single MCP tool call and receive bounded, UTF-8 text for explanation.

A very simple vector store that provides capability to watch a list of directories, and automatically index all the markdown, html and text files in the directory to a vector store to enhance context.

Enables managing local Markdown notes by creating, viewing, listing, and searching notes and their contents through MCP tools.

Provides a complete end-to-end MCP server implementation with file system tools, web scraping capabilities, and system information access. Includes ready-to-use configuration files and integration examples for Claude Desktop, ChatGPT, and other AI models.

A simple MCP server that provides basic utility tools for text manipulation, file operations, and calculations, intended to be connected to Claude AI desktop app.

Enables AI agents to autonomously navigate a codebase by listing directories, reading files, searching code, and running whitelisted commands.

A TypeScript-based MCP server that enables Claude Desktop to perform file operations and retrieve system information, with built-in security features that restrict access to safe directories only.

Provides PDF analysis, data extraction, form filling, and comparison capabilities for Claude and Cursor, supporting both text and scanned documents with OCR.

A straightforward task management system enabling sequential task tracking, completion, and progress management through simple function calls or natural language commands.

A proof-of-concept MCP server that enables reading local files and performing basic arithmetic operations. It provides a simple foundation for understanding how tools are exposed to MCP clients.

A minimal MCP server providing tools for time, calculations, sandboxed file operations, and safe URL fetching over stateless HTTP.

Provides secure filesystem access for AI models through the Model Context Protocol with strict path validation, file operations, directory management, and system command execution within predefined directories.

Provides comprehensive document processing, including reading, converting, and manipulating various document formats with advanced text and HTML processing capabilities.

An HTTP MCP server that indexes large documents into exact-line-numbered sections, enabling AI models to locate, read, summarize, and edit parts of a document without ingesting the whole file.

Enables natural language filesystem operations (create, list, delete directories/files) via Ollama local LLM and MCP protocol within allowed directories.

Enables interaction with the WhkerDB shared PDF editor to manage collaborative rooms, file structures, and real-time annotations. It allows users to upload PDFs and images, manage note trees, and sync data across platforms through natural language.

Provides a secure workspace for AI-driven file management and Python script execution designed to run on Vercel. It enables tools for full file operations and code execution within a sandboxed environment.

Enables AI models to fetch GitHub repository information, read file contents, and search local documentation.

SSH orchestration MCP server for coding agents, enabling persistent bash sessions, hash-protected remote file editing, SFTP transfers, SSH tunnels, and multi-host orchestration with connection reuse across tools.