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.
@vivek100
基本信息
This helps you create a mcp server which your IDE can access to create and save prompts for you code base
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"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
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。
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.
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.
It saves and versions custom AI prompts for your code repositories, seamlessly integrating with AI-powered IDEs like Cursor and GitHub Copilot.
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.
Backend: `LAYER_API_KEY` and `LAYER_BASE_URL`. Frontend: `NEXT_PUBLIC_API_URL` pointing to the backend server.
Yes. Each prompt can have multiple versions with change notes. You can compare and restore previous versions.
Yes. You can use pre-existing templates and create your own to standardize AI interactions across your team.
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