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system-prompts-mcp-server

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Model Context Protocol server exposing system prompt files and summaries.

๐Ÿ”ฅ๐Ÿ”ฅโœ“ VerifiedFreeAdvanced setup

๐Ÿ“ System Prompts MCP Server

Access system prompts from AI tools in your workflow. Browse and fetch prompts from Devin, Cursor, Claude, GPT, and more. Model-aware suggestions help you find the perfect prompt for your LLM.

An MCP (Model Context Protocol) server that exposes a collection of system prompts, summaries, and tool definitions from popular AI tools as MCP tools for AI coding environments like Cursor and Claude Desktop.

Why Use System Prompts MCP?

  • ๐Ÿ” Automatic Discovery โ€“ Every prompt in prompts/ is automatically exposed as an MCP tool
  • ๐ŸŽฏ Model-Aware Suggestions โ€“ Get prompt recommendations based on your LLM (Claude, GPT, Gemini, etc.)
  • ๐Ÿ“š Comprehensive Collection โ€“ Access prompts from Devin, Cursor, Claude, GPT, and more
  • ๐Ÿš€ Easy Setup โ€“ One-click install in Cursor or simple manual setup
  • ๐Ÿ”ง Extensible โ€“ Add your own prompts and they're automatically available

Features

Core Tools

  • list_prompts โ€“ Browse available prompts with filters (service, flavor, provider)
  • get_prompt_suggestion โ€“ Get ranked prompt suggestions for your LLM and keywords
  • <service>-<variant>-<flavor> โ€“ Direct access to any prompt (e.g., cursor-agent-system, devin-summary)

Automatic Discovery

  • Scans prompts/ directory for .txt, .md, .yaml, .yml, .json files
  • Each file becomes a dedicated MCP tool
  • Infers metadata (service, variant, LLM family, persona hints)

Persona Activation

  • Each tool call includes a reminder for the model to embody the loaded prompt
  • Helps models behave like the original service (Devin, Cursor, etc.)

Adding Your Own Prompts

Add prompts by placing files in the prompts/ directory:

Supported formats: .txt, .md, .yaml, .yml, .json

Directory structure:

prompts/My Service/
  โ”œโ”€โ”€ System Prompt.txt     โ†’ Tool: "my-service-system-prompt-system"
  โ””โ”€โ”€ tools.json            โ†’ Tool: "my-service-tools-tools"
  • Directory names become the service name
  • File names create tool variants
  • Files are automatically classified as system prompts, tools, or summaries

After adding prompts, restart the MCP server. Use list_prompts to find your custom prompts.

Custom directory: Set PROMPT_LIBRARY_ROOT environment variable to use a different location.

Use Cases

  • AI Tool Developers โ€“ Reference and adapt prompts from successful AI tools
  • Researchers โ€“ Study how different tools structure their system prompts
  • Developers โ€“ Find the perfect prompt for your LLM and use case
  • Prompt Engineers โ€“ Compare and learn from proven prompt patterns

Technical Details

Built with: Node.js, TypeScript, MCP SDK
Dependencies: @modelcontextprotocol/sdk, zod
Platforms: macOS, Windows, Linux

Environment Variables:

  • PROMPT_LIBRARY_ROOT (optional): Override prompt root directory (defaults to prompts/)

Project Structure:

  • src/ โ€“ TypeScript MCP server implementation
  • dist/ โ€“ Compiled JavaScript
  • prompts/ โ€“ Prompt library and original documentation

Support

If you find this project useful, consider supporting it:

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