AI Prompts

Model Context Protocl for AI Prompts API

typescript

18

GitHub Stars

typescript

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "instructa-ai-prompts-mcp": {
      "command": "pnpm",
      "args": [
        "start:mcp"
      ]
    }
  }
}

You can run and manage an MCP (Model Context Protocol) server that serves and orchestrates AI prompts using a TypeScript-based, monorepo-oriented workflow. This MCP server lets you start a prompt-serving backend locally, build it for production, and configure environment-specific settings to suit your deployment needs.

How to use

To operate the MCP server, install dependencies, set up your environment, and start the production-ready server. You will use a local runtime command to start the MCP service and, when needed, build or run in development mode for testing. Your client applications can connect to the MCP endpoint to manage prompts, contexts, and related actions in a structured way.

How to install

Prerequisites: ensure you have a supported Node.js LTS version installed and the pnpm package manager available on your system.

Step by step commands to set up and run the MCP server:

# 1) Clone the project
git clone https://github.com/yourusername/instructa-ai.git
cd instructa-ai

# 2) Install dependencies
pnpm install

# 3) Set up environment variables
cp packages/mcp/.env.dist packages/mcp/.env
# Edit packages/mcp/.env with your configuration

# 4) Run the MCP development server (optional)
pnpm run dev:mcp

# 5) Build the MCP package
pnpm run build:mcp

# 6) Start the MCP production server
pnpm run start:mcp

Configuration and running notes

The MCP server is configured via environment files located under the MCP package. Copy the example environment file and tailor the values for your deployment. The following commands demonstrate the standard flow from development to production.

Additional notes

Environment-based configuration is used to tailor the MCP server behavior per deployment. Maintain separate .env files for development, staging, and production as needed. The MCP server supports standard development, build, and start workflows via the provided npm/pnpm scripts.