Layer Prompt Manager MCP Server

@vivek100

Repository

Basic information

About Layer Prompt Manager MCP Server

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

Layer Prompt Manager MCP Server config

Add this server to your MCP-compatible client using the configuration below.

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

Layer Prompt Manager MCP Server tools

Tool list not available yet

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Overview

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.

Frequently asked questions

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.

Comments

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