MCP Prompt Engine

Overview

The MCP Prompt Engine is a lightweight, Go‑based server that turns ordinary text files into fully dynamic prompt templates for any Model Context Protocol (MCP) compatible AI client. By leveraging the native Go engine, it gives developers a familiar and powerful syntax for constructing prompts that can include variables, conditionals, loops, and reusable partials. Each template automatically exposes its variables as MCP prompt arguments, so clients can supply contextual data at runtime without any additional plumbing.

What sets this server apart is its focus on prompt lifecycle management. It watches a designated directory for changes, hot‑reloading templates whenever they are edited. This eliminates the need to restart the server during iterative development, dramatically speeding up experimentation with new prompt designs. The accompanying CLI provides quick validation, rendering previews, and a list of available templates, making it easy to catch syntax errors before they reach the AI model.

The engine’s argument handling is particularly developer‑friendly. It parses JSON payloads into native Go types, supports arrays and nested objects, and automatically falls back to environment variables when arguments are omitted. This allows prompts to be driven by both explicit client input and local configuration, a pattern that is common in CI/CD pipelines or local tooling integrations.

Typical use cases include building reusable prompt libraries for code generation, documentation, or data analysis. For example, a team could maintain a set of partials for consistent Git commit messages or code review guidelines and then let the server render them with project‑specific details. Because the server speaks MCP, it can be plugged into any client that supports prompts—Claude Code, Gemini CLI, VSCode Copilot, or even custom scripts—without any client‑side changes.

In short, the MCP Prompt Engine provides a robust, developer‑centric workflow for creating, validating, and deploying dynamic prompts. Its combination of Go template power, hot‑reload convenience, and seamless MCP integration makes it an essential tool for teams looking to standardize prompt logic while keeping the flexibility needed for real‑world AI applications.