"Enhancing Prompt Engineering with MCP" 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.

Connects LLMs to Israeli civil engineering databases, including the Blue Book specs, Dekel 2026 pricing, Excel BOQ parsing, and tender arbitrage for unbalanced bidding.

MCP server for professional prompt engineering and agentic scaffolding, with cloud and local optimization.

Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.

Fix your vibe coding prompts before they reach the AI. Scores and rewrites across 4 dimensions — no API key, no server, just npx. Now with codebase-aware context injection for design, database, API, auth, testing, and state management.

Enables coding agents to load NASA-derived software-engineering rules before implementation, dynamically expand them as scope changes, and enforce an evidence-based final review gate.

MCP server for managing and serving dynamic prompt templates using elegant and powerful text template engine. Create reusable, logic-driven prompts with variables, partials, and conditionals that can be served to any compatible MCP client like Claude Code, Claude Desktop, Gemini CLI, etc.

A deterministic prompt optimization middleware for AI coding agents that preserves intent, compresses context, and detects drift, available as an MCP server with tools for optimize_prompt, classify_prompt, and more.

Git-driven MCP server that manages and provides prompt templates with Handlebars support, enabling teams to collaborate on and version-control reusable, dynamic prompts across AI editors like Cursor and Claude Desktop.

Provides MCP clients a single decision-only tool to classify prompts as safe for local or cloud models, or as containing PII or jailbreak content, without executing actions or calling AI models.

Lets Claude read and write Prompt Studio projects as Flow text, with version history and a repo-synced .flow file.

This MCP server enables searching Korean construction standards (KDS/KCS), laws from the Ministry of Government Legislation, administrative rules and interpretations, and optionally local water/wastewater design manuals to generate grounded evidence packages for engineering answers.

A unified MCP Gateway for enterprise knowledge, code, and memory tools, featuring admin management for documents, accounts, and MCP keys, with local network deployment support.

Provides stateful prompt optimization using research-backed techniques like APE and OPRO, learning from historical performance data via a vector database. It enables users to automatically refine prompts, retrieve high-performing examples, and track performance analytics through iterative feedback.

WAF for AI agents — block prompt injection before it reaches the LLM.

Enables Claude to receive physical touch events from a phone via the PWA and respond with text, haptic vibrations, and expression changes, giving an AI companion embodied presence through touch.

Enhances and cleans raw prompts using AI to make them more clear, actionable, and effective. Provides quality assessment, suggestions, and supports both general and code-specific optimization modes.

Allows MCP clients to create, validate, preview, and submit product showcases on Build with AK, with support for local stdio and remote HTTP transports.

Provides retrieval-augmented generation (RAG) capabilities by ingesting various document formats into a persistent ChromaDB vector store. It enables semantic search and retrieval using either OpenAI or Ollama embeddings for processing local files, directories, and URLs.

A Model Context Protocol server that helps users create, validate, manage, and optimize prompts using the RISEN framework (Role, Instructions, Steps, Expectations, Narrowing).