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Layer Prompt Manager

@vivek100

代码仓库

关于 Layer Prompt Manager

This helps you create a mcp server which your IDE can access to create and save prompts for you code base

#codepromptmanager#prompt-management#ai-integration

基本信息

分类

开发工具

许可证

MIT

运行时

node

传输方式

stdio

发布者

vivek100

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "codePromptManagerMCP": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        "venv"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Layer Prompt Manager?

Layer Prompt Manager is an MCP server that saves, versions, and manages custom AI prompts for code repositories. It integrates with AI-powered IDEs like Cursor and GitHub Copilot, connecting your development environment to the Layer platform.

How to use Layer Prompt Manager?

Set up the backend (Python 3.8+, SQLite) and frontend (Node.js v16+), configure environment variables (LAYER_API_KEY, LAYER_BASE_URL, NEXT_PUBLIC_API_URL), then use the web UI to create, edit, version, and manage prompts and templates.

Key features of Layer Prompt Manager

  • Save prompts directly from your AI-powered IDE.
  • Version control for prompts with change notes.
  • Create, edit, and manage Layer prompts.
  • Pre-built and custom templates for team standardization.
  • Modern matrix-inspired dark mode UI.

Use cases of Layer Prompt Manager

  • Build a library of effective prompts specific to your codebase.
  • Standardize AI interactions across your development team.
  • Track prompt evolution and compare different versions.
  • Roll back to previous prompt versions when needed.
  • Share and reuse common prompt patterns with templates.

FAQ from Layer Prompt Manager

What is Layer Prompt Manager?

It saves and versions custom AI prompts for your code repositories, seamlessly integrating with AI-powered IDEs like Cursor and GitHub Copilot.

How do I set up Layer Prompt Manager?

Requires Node.js v16+, Python 3.8+, pip, and SQLite. Backend uses FastAPI; frontend uses Next.js. You need a Layer API key and base URL.

What environment variables are needed?

Backend: LAYER_API_KEY and LAYER_BASE_URL. Frontend: NEXT_PUBLIC_API_URL pointing to the backend server.

Can I manage versions of prompts?

Yes. Each prompt can have multiple versions with change notes. You can compare and restore previous versions.

Is there a template system?

Yes. You can use pre-existing templates and create your own to standardize AI interactions across your team.

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