"Understanding Prompts or Prompt Engineering" matching MCP servers:

Enables ChatGPT to interact with Engineering MCP through a secure MCP endpoint, including executing C2C plans and workspace file access with operator approval.

Enables AI models like Claude to manage local prompt files with CRUD operations, fuzzy search, categorization, templates, version control, and favorites.

Provides custom prompts for Amazon Q by serving markdown files from the local filesystem as prompt templates through the Model Context Protocol.

Enables AI agents to safely inspect, edit, and test code within a bounded repository environment to solve software engineering tasks and verify fixes.

A lightweight, file-based server for managing and serving personal prompt templates with variable substitution support via the Model Context Protocol. It allows users to store, update, and organize prompts in a local directory through integrated MCP tools and CLI assistants.

Records approved parking reservations to a secure text file via the Model Context Protocol, with token authentication and input sanitization.

Convert technical-drawing PDFs and engineering callouts between metric and imperial — values stamped in place, threads cross-referenced, shop-floor rounding.

MCP server for TQS structural engineering CAD/analysis software, enabling Claude to read building models, extract drawing data, run structural processing, and script against the TQS API.

A security-first MCP server that provides LLMs with structured tools for filesystem, process, search, build/test/lint, IDE integration, and more.

Enables loading and serving markdown files as prompts from local folders or GitHub repositories. Supports automatic repository synchronization and YAML frontmatter for prompt metadata.

Provides tools, resources, and prompts for managing a local Markdown notes database, including create, read, update, delete, search, and statistics operations, with robust path traversal protection.

MCP server that enforces single-use human confirmations for sensitive tool calls, sanitizes prompts against prompt injection, and re-validates file paths before destructive actions.

A demonstration MCP server showcasing tools (calculator, file operations, weather, timestamp), resources (server config, system info, documentation), and reusable prompt templates for code review, documentation, and debugging.

Combines codebase files into a single prompt for AI assistants, enabling code review, documentation, and debugging via natural language.

A Node.js MCP server that enables LLM tools to list and read local guide and prompt files for Creatio development, facilitating seamless communication between AI assistants and Creatio-specific documentation.

A secure MCP server with a workspace sandbox for AI agents to manage prompts, save HTML, and render HTML to images.

An MCP-native journaling server that prompts one question per day and captures your responses verbatim, with no AI rewriting or analysis. It integrates with Claude Desktop, Cline, or cron scripts, storing everything as markdown in your vault.

Provides a production-ready Model Context Protocol server with dual STDIO and Streamable HTTP transports, enabling file operations, memory, database queries, RAG, web search, GitHub integration, background tasks, and prompt-based workflows.

A modular framework for building and running multiple MCP servers with file operations, system information, and extensible tool/prompt/resource support.

Enables AI agents to inspect and operate a UGOS Pro NAS through its built-in HTTPS API via 25 tools covering system stats, storage volumes, files, downloads, photos, and media libraries, without SSH. Read-only tools run directly, write tools prompt for confirmation, destructive deletes require an explicit second confirmation, and it can be deployed either locally over stdio or on the NAS via Docker SSE.