list_promptsLABSCO SUMMARY
A prompt library your assistant can reach into mid-session.
Reading somebody's published system prompt teaches you something; loading it as the working instructions teaches you more. Because every file in the directory becomes a tool automatically, the same server doubles as the place to keep your own prompts.
What it is
A server that exposes a collection of published system prompts, summaries and tool definitions from well-known AI tools. Every file in its prompts directory becomes a tool of its own — named service-variant-flavour, such as cursor-agent-system or devin-summary — alongside two calls for browsing and picking one. Each call returns the prompt with a reminder for the model to adopt it.
What you get
- The available prompts browsed, filtered by service, flavour or provider
- Ranked suggestions for your LLM and your keywords, so the pick is matched to the model you are on
- Direct access to any individual prompt as its own tool
- Automatic discovery: .txt, .md, .yaml, .yml and .json files dropped into the prompts directory become tools, with service, variant and LLM family inferred
- Your own prompts added the same way, without touching the server code
Requirements
A recent Node.js. The README's npm name, system-prompts-mcp-server, is not on the registry, and its one-click Cursor link runs that same name, so it is built from a clone. No account and no key — the prompts ship with the repository.
Setup effort
Build from source — git clone https://github.com/JamesANZ/system-prompts-and-models-of-ai-tools.git
USE CASES
01
Seeing what is in the collection
Browse the prompts filtered by service, flavour or provider before picking one to load.
02
Picking a prompt that suits the model you are using
Get ranked suggestions for your LLM and the keywords describing the task, rather than guessing from the file names.
03
Studying how a well-known agent is instructed
List what exists for that service and open the variant you want to read.
04
Keeping your own prompts where the assistant can load them
Drop the file into the prompts directory, then find it in the listing like any other.
2 tools
Listed in project docs. Your client may show a different list.
get_prompt_suggestionBEFORE YOU INSTALL
What to know first
Tools you get
2 tools named in the project's documentation.
Where it runs
The documented client runs the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
# Clone and build
git clone https://github.com/JamesANZ/system-prompts-and-models-of-ai-tools.git
cd system-prompts-and-models-of-ai-tools
npm install
npm run buildMCP Clients
Claude Desktop
CLAUDE DESKTOP · JSON
{
"mcpServers": {
"system-prompts-mcp": {
"command": "node",
"args": [
"<YOUR_PATH_TO_SYSTEM_PROMPTS_AND_MODELS>/dist/index.js"
],
"env": {
"PROMPT_LIBRARY_ROOT": "<YOUR_PATH_TO_SYSTEM_PROMPTS_AND_MODELS>/prompts"
}
}
}
}
