MCP Prompt Engine
M

MCP Prompt Engine

A server based on the Model Control Protocol (MCP) for managing and providing dynamic prompt templates. It utilizes the powerful Go text template engine, supports variables, conditions, loops, and reusable components, allows the creation of logic-driven prompt templates, and can seamlessly integrate with MCP-compatible clients such as Claude and Gemini.
2.5 points
6.9K

What is MCP Prompt Engine?

MCP Prompt Engine is an intelligent prompt management server that allows you to create, manage, and reuse complex prompt templates. Through the Model Context Protocol (MCP) standard, it can seamlessly integrate with various AI assistant clients (such as Claude Desktop, Gemini CLI, VSCode Copilot, etc.), enabling you to quickly call well-designed prompt templates and improve work efficiency.

How to use MCP Prompt Engine?

Using MCP Prompt Engine is very simple: 1) Install the server program; 2) Create your prompt template files; 3) Configure the server in your AI assistant client; 4) Directly call your custom prompts in the client. The entire process does not require writing complex code. You can create powerful prompt logic using simple template syntax.

Use Cases

MCP Prompt Engine is particularly suitable for the following scenarios: developer teams that need to reuse complex prompts, individual users who want to standardize the workflow of AI assistants, application scenarios that require dynamic generation of prompt content, and users who want to share prompt templates among multiple AI tools.

Main Features

MCP Protocol Compatible
Fully compatible with the Model Context Protocol standard, it can work seamlessly with all MCP-supported clients (Claude, Gemini, Copilot, etc.) without additional adaptation.
Powerful Go Template Engine
Using the text/template engine of the Go language, it supports advanced functions such as variables, conditional judgments, loops, and functions, making prompt templates more intelligent and flexible.
Reusable Components
Supports creating partial templates (partials), such as _header.tmpl, which can be reused in multiple prompts to maintain consistency and reduce duplicate work.
Dynamic Parameter Support
Template variables are automatically converted into MCP prompt parameters, allowing users to dynamically input values when calling, and supporting complex data types in JSON format.
Hot Reload
Automatically detects changes in template files and reloads them. You can update prompts without restarting the server, improving development efficiency.
Rich Command-Line Tools
Provides a complete CLI tool that can list, validate, and render templates, facilitating development and testing.
Smart Parameter Processing
Automatically parses JSON parameters (booleans, numbers, arrays, objects) and supports environment variables as parameter fallback values.
Docker Containerization
Provides complete Docker support, facilitating deployment and integration into various environments.
Advantages
Out-of-the-box: Easy to install and ready to use after configuration.
Cross-platform compatible: Supports all major operating systems and AI assistant clients.
Powerful template functions: Supports complex logic and data processing.
Developer-friendly: Provides a complete CLI tool and hot reload function.
Flexible deployment: Supports local operation and Docker containerized deployment.
Active community: Based on an open-source project, with continuous updates and maintenance.
Limitations
Requires basic technical knowledge: Configuring the MCP server requires a certain technical background.
Learning curve for Go templates: Advanced template functions require learning Go template syntax.
Depends on MCP clients: Must use AI assistants that support the MCP protocol.
Initial configuration is complex: The first setup requires multiple steps.
Resource consumption: Running as an independent server requires a certain amount of system resources.

How to Use

Install MCP Prompt Engine
Choose the appropriate installation method according to your operating system. It is recommended to use Go to install or download the pre-compiled binary file.
Create a Prompt Template Directory
Create a prompts folder in your project or working directory to store all prompt template files.
Write Your First Prompt Template
Create a .tmpl file and write your prompt using Go template syntax. The first line comment will be used as the prompt description.
Validate Template Syntax
Use the CLI tool to validate whether the template has syntax errors and ensure that the template can be used normally.
Configure the MCP Client
Add the MCP server configuration to the configuration file of your AI assistant client (such as Claude Desktop).
Start the Server and Use
Start the MCP server and then call the configured prompt template in your AI assistant.

Usage Examples

Git Commit Message Generator
Create an intelligent Git commit message generation prompt that automatically generates commit messages conforming to the Conventional Commits specification based on code changes.
Code Review Assistant
Create a standardized code review checklist to ensure that all important aspects are covered in each code review.
API Documentation Generator
Automatically generate API interface documentation templates based on the code to keep the documentation in sync with the code.

Frequently Asked Questions

Which AI assistant clients does MCP Prompt Engine support?
Do I need to learn the Go language to use the templates?
Where should the template files be placed?
How to debug template issues?
Does it support team collaboration?
How is the performance? Will it affect the speed of the AI assistant?

Related Resources

GitHub Repository
Project source code, issue tracking, and latest version releases
Model Context Protocol Official Documentation
Complete specification of the MCP protocol and list of client support
Go Template Syntax Guide
Official documentation and syntax reference for the Go language text/template package
Claude Desktop Configuration Guide
How to configure the MCP server in Claude Desktop
Example Template Library
Template examples for various practical scenarios that can be used directly or as a reference

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

Alternatives

R
Rsdoctor
Rsdoctor is a build analysis tool specifically designed for the Rspack ecosystem, fully compatible with webpack. It provides visual build analysis, multi - dimensional performance diagnosis, and intelligent optimization suggestions to help developers improve build efficiency and engineering quality.
TypeScript
9.0K
5 points
N
Next Devtools MCP
The Next.js development tools MCP server provides Next.js development tools and utilities for AI programming assistants such as Claude and Cursor, including runtime diagnostics, development automation, and document access functions.
TypeScript
8.6K
5 points
T
Testkube
Testkube is a test orchestration and execution framework for cloud-native applications, providing a unified platform to define, run, and analyze tests. It supports existing testing tools and Kubernetes infrastructure.
Go
6.2K
5 points
M
MCP Windbg
An MCP server that integrates AI models with WinDbg/CDB for analyzing Windows crash dump files and remote debugging, supporting natural language interaction to execute debugging commands.
Python
9.8K
5 points
R
Runno
Runno is a collection of JavaScript toolkits for securely running code in multiple programming languages in environments such as browsers and Node.js. It achieves sandboxed execution through WebAssembly and WASI, supports languages such as Python, Ruby, JavaScript, SQLite, C/C++, and provides integration methods such as web components and MCP servers.
TypeScript
7.6K
5 points
P
Praisonai
PraisonAI is a production-ready multi-AI agent framework with self-reflection capabilities, designed to create AI agents to automate the solution of various problems from simple tasks to complex challenges. It simplifies the construction and management of multi-agent LLM systems by integrating PraisonAI agents, AG2, and CrewAI into a low-code solution, emphasizing simplicity, customization, and effective human-machine collaboration.
Python
7.4K
5 points
N
Netdata
Netdata is an open-source real-time infrastructure monitoring platform that provides second-level metric collection, visualization, machine learning-driven anomaly detection, and automated alerts. It can achieve full-stack monitoring without complex configuration.
Go
9.7K
5 points
M
MCP Server
The Mapbox MCP Server is a model context protocol server implemented in Node.js, providing AI applications with access to Mapbox geospatial APIs, including functions such as geocoding, point - of - interest search, route planning, isochrone analysis, and static map generation.
TypeScript
8.8K
4 points
G
Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
21.1K
4.3 points
N
Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
19.3K
4.5 points
D
Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
63.2K
4.3 points
M
Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
31.5K
5 points
U
Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
27.2K
5 points
F
Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
59.4K
4.5 points
C
Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
85.7K
4.7 points
G
Gmail MCP Server
A Gmail automatic authentication MCP server designed for Claude Desktop, supporting Gmail management through natural language interaction, including complete functions such as sending emails, label management, and batch operations.
TypeScript
20.1K
4.5 points
AIBase
Zhiqi Future, Your AI Solution Think Tank
© 2026AIBase