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NAP MCP Server

@alphagroup-ai

关于 NAP MCP Server

暂无概览

基本信息

分类

其他

运行时

node

传输方式

stdio

发布者

alphagroup-ai

配置

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代码仓库

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概览

What is NAP MCP Server?

It is a Model Context Protocol (MCP) server that provides a standardized way to interact with NAP API endpoints through MCP tools and resources, including prompts. It is intended for developers who want to create projects, manage applications and clients, and import/export workflows via MCP.

How to use NAP MCP Server?

Clone the repository, install dependencies with pnpm install, copy .env.example to .env, and update the environment variables with your NAP API configuration. In Cursor editor, add a new MCP server with the command node and args ["./nap-mcp-server/index.js"]. After making changes, run npx tsc to compile JavaScript.

Key features of NAP MCP Server

  • Create projects, applications, clients, and workflows through MCP.
  • Import and export workflows between projects.
  • Create workflows using prompts.
  • Standardized interaction with NAP API via MCP tools and resources.

Use cases of NAP MCP Server

  • Automating creation of NAP projects and their components.
  • Replicating workflows from one project to another via export/import.
  • Using prompts to generate workflows quickly within a project.
  • Integrating NAP API capabilities into AI‑assisted development workflows.

FAQ from NAP MCP Server

What does NAP MCP Server integrate with?

It integrates with the NAP API through the Model Context Protocol, allowing interaction with NAP endpoints via MCP tools and resources.

How do I install and configure the server?

Clone the repo, run pnpm install, copy .env.example to .env, and fill in your NAP API configuration. For Cursor, add the server using the command node and args ["./nap-mcp-server/index.js"].

What are the runtime requirements?

The server requires Node.js, a JavaScript runtime, to execute the index.js entry point. It also needs the MCP client (e.g., Cursor) to be properly configured.

Where does the configuration data live?

The NAP API configuration is stored in a .env file in the project root, using environment variables for credentials and endpoints.

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