How do I install and run Prompt Manager?
Clone the repository, then set up the environment using `task setup:py`, `task setup:js` (or `make setup`), and run `./bin/start_prompt_manager.sh`. Open `http://localhost:8081` in a browser.
@appositeit
基本信息
A web and API-based system for managing, composing, and organizing AI prompts, with an MCP server for intetgration with common AI pltforms (Claude Desktop, Cursor, Windsurf, etc.).
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。
Prompt Manager is a standalone system for managing AI prompts with composable elements. It provides a web interface and RESTful API for creating, organizing, and editing prompts, and integrates with the Model Context Protocol (MCP) for advanced prompt workflows. It targets users who need efficient, keyboard-driven prompt management.
Clone the repository, set up the environment using the provided Taskfile (recommended) or Makefile, then run the startup script. Access the web UI at http://localhost:8081 or use the REST API endpoints programmatically. For real-time editing, connect via WebSocket to /api/prompts/ws/{prompt_id}.
Clone the repository, then set up the environment using `task setup:py`, `task setup:js` (or `make setup`), and run `./bin/start_prompt_manager.sh`. Open `http://localhost:8081` in a browser.
Prompts are stored in the project data directory (`prompt_manager/data/prompts/`) and the user config directory (`~/.prompt_manager/prompts/`).
Prompt Manager offers a RESTful API for CRUD operations on prompts and directories, a WebSocket interface for real-time editing, and integration with the Model Context Protocol (MCP) for advanced workflows.
The README does not mention any authentication mechanism for the web interface or API.
The setup requires Python and JavaScript environments, managed via a Taskfile or Makefile. The application runs on localhost port 8081 by default.
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