by seungwonme
Prompt Library saves and organizes prompts as local markdown files, creating a personal prompt library across sessions f
Saves prompts as timestamped markdown files in a local directory and lets you list them later. Builds a persistent personal prompt collection that survives across chat sessions.
Prompt Library is a community-built MCP server published by seungwonme that provides AI assistants with tools and capabilities via the Model Context Protocol. Prompt Library saves and organizes prompts as local markdown files, creating a personal prompt library across sessions f It is categorized under productivity. This server exposes 2 tools that AI clients can invoke during conversations and coding sessions.
You can install Prompt Library in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Prompt Library is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
According to our notes, Prompt Library benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Prompt Library has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Prompt Library is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated Prompt Library against two servers with overlapping tools; this profile had the clearer scope statement.
Prompt Library reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
I recommend Prompt Library for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Strong directory entry: Prompt Library surfaces stars and publisher context so we could sanity-check maintenance before adopting.
We evaluated Prompt Library against two servers with overlapping tools; this profile had the clearer scope statement.
Prompt Library is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Useful MCP listing: Prompt Library is the kind of server we cite when onboarding engineers to host + tool permissions.
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A Model Context Protocol (MCP) server for saving and managing prompts. This tool allows you to save prompts with timestamps and list previously saved prompts.
You can run this MCP server directly using npx without installation:
npx prompt-new-mcp
Add this server to your Claude Desktop configuration:
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"prompt-new-mcp": {
"command": "npx",
"args": ["-y", "prompt-new-mcp"]
}
}
}
Edit %APPDATA%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"prompt-new-mcp": {
"command": "npx",
"args": ["-y", "prompt-new-mcp"]
}
}
}
Saves a prompt with a timestamp to the prompts directory.
Parameters:
name (string): The name for the prompt filecontent (string): The prompt content to saveLists saved prompts in the prompts directory.
Parameters:
limit (number, optional): Maximum number of prompts to return (default: 20)Prompts are saved in the prompts directory with the following naming convention:
YYYYMMDD_HHMMSS_<sanitized-name>.md
Example: 20250125_143022_user-question.md
MIT
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.