AI Prompts Finder

An AI prompt management service based on TypeScript, adopting the MCP protocol and pnpm monorepo architecture.

Artificial intelligence chatbots Developer tools #AI prompts #Protocol management #Monorepo architecture Local .TypeScript

rating : 2.5 points

downloads : 11

update time : 2025-04-28

What is Instructa AI - MCP Prompts API?

Instructa AI - MCP Prompts API is a toolset for managing and providing AI prompts. It enables efficient data interaction through the Model Context Protocol (MCP) and supports various application scenarios.

How to use Instructa AI - MCP Prompts API?

Users can quickly get started through simple installation and configuration steps, and use the command-line tool to start the development or production environment server.

Applicable scenarios

Suitable for application scenarios that require automated generation of high-quality AI prompts, such as content creation, customer service conversations, data analysis, etc.

Main features

MCP protocol supportAdopt the Model Context Protocol to ensure efficient and stable model context transfer.

Multi-language supportSupport integration with multiple programming languages and frameworks to meet the needs of different developers.

Flexible configurationEasily configure server running parameters, such as port, log level, etc., through environment variables.

Advantages and limitations

Advantages

High-performance model context processing capability

Open source and free, with active community support

Limitations

There may be a slight delay on low-bandwidth networks

Advanced features require a certain technical level

How to use

Clone the repository

Use Git to clone the project to your local machine.

Install dependencies

Use pnpm to install the required dependency packages for the project.

Configure environment variables

Copy the default configuration file and modify it as needed.

Start the service

Run the development or production mode command.

Usage examples

Content generation exampleUse the MCP Prompts API to generate a news summary.

Customer service conversation optimizationProvide a more intelligent response strategy for customer service robots.

Frequently Asked Questions

How to start using Instructa AI - MCP Prompts API?

Does it support custom prompts?

Related resources

Official documentation

Detailed API documentation and tutorials.

GitHub code repository

Source code and contribution guidelines.

X/Twitter

Official social media account.

🚀 Instruction AI - MCP Prompt API

This repository contains an implementation of the Model Context Protocol (MCP) for managing and serving AI prompts. The project is written in TypeScript and uses a monorepo structure with pnpm workspaces.

🚀 Quick Start

This project provides a Model Context Protocol (MCP) implementation for AI prompt management. It's built with TypeScript and organized as a monorepo using pnpm workspaces.

✨ Features

MCP (Model Context Protocol) Implementation: Enables efficient management of AI prompt contexts.
TypeScript-based Architecture: Ensures type safety and maintainability.
Monorepo Structure with pnpm Workspaces: Facilitates code organization and dependency management.
Environment Configuration Support: Allows for easy customization of the runtime environment.

📋 Prerequisites

Node.js: It is recommended to use the LTS version.
pnpm: A fast, disk space efficient package manager.

📦 Installation

Clone the repository:

git clone https://github.com/yourusername/instructa-ai.git
cd instructa-ai

Install dependencies:

pnpm install

Set up environment variables:

cp packages/mcp/.env.dist packages/mcp/.env
# Edit the .env file to configure your settings

💻 Usage Examples

Basic Usage

To start the development server:

# Start the MCP development server
pnpm dev:mcp

# Build the MCP package
pnpm build:mcp

# Start the MCP production server
pnpm start:mcp

Project Structure

.
├── packages/
│   └── mcp/          # MCP implementation package
│       ├── src/      # Source code
│       └── .env      # Environment configuration file
├── package.json      # Root package.json
└── pnpm-workspace.yaml

🤝 Contribution

Contributions, issues, and feature requests are welcome! Please feel free to check the issues page.

🌐 Social Media

X/Twitter: @kregenrek
Bluesky: @kevinkern.dev

📄 License

This repository is open-source and licensed under the MIT License. You are free to use, modify, and distribute it under the following conditions: adhere to these terms. Happy building!