MCP 服务器

Teleprompter

Enables storage and reuse of prompt templates with variable substitution for LLMs. Supports creating, searching, and retrieving prompt templates to avoid repeating complex instructions across conversations.

README

Teleprompter

An MCP server that manages and exposes tools to allow prompt re-use with LLMs.

Features
MCP Configuration
Usage Examples
Environment Variables
Testing
Contributing
License
Acknowledgements

Features

Prompt Storage & Reuse: Store, search, and retrieve prompt templates for LLMs.
MCP Server: Exposes prompt tools via the Model Context Protocol (MCP).
Prompt Variables: Supports template variables (e.g., {{name}}) for dynamic prompt generation.
Search: Fast full-text search over stored prompts using MiniSearch.
TypeScript: Modern, type-safe codebase.
Extensive Testing: Includes unit and integration tests with Vitest.

MCP Configuration

To use Teleprompter with your LLM client, add this configuration:

{
  "mcpServers": {
    "teleprompter": {
      "command": "npx",
      "args": ["-y", "mcp-teleprompter"],
      "env": {
        "PROMPT_STORAGE_PATH": "/path/to/your/prompts-directory"
      }
    }
  }
}

Note: Replace /path/to/your/prompts-directory with the absolute path where you want prompts stored.

Usage Examples

Once configured, you can use Teleprompter with your LLM by using prompt tags in your conversations. Here's a detailed example that shows how it solves the problem of repeating complex instructions:

🎵 Music Discovery on Spotify

The Problem: Every time you want music recommendations, you have to remind your LLM of all your preferences and constraints:

"Don't suggest songs I already have in my playlists"
"Avoid explicit lyrics"
"Add songs to my queue for review, not directly to playlists"
"Focus on discovering new artists, not just popular hits"
"Consider my current activity and mood"
"Provide brief explanations for why each song fits"

The Solution: Create a prompt that captures all these instructions once.

Creating the prompt: Ask your LLM: "Create a prompt called 'spotify-discover' that helps me find new music with all my specific preferences and workflow requirements."

This creates a comprehensive template like:

I'm looking for music recommendations for Spotify based on:

**Current mood:** {{mood}}
**Activity/setting:** {{activity}}
**Preferred genres:** {{genres}}
**Recent artists I've enjoyed:** {{recent_artists}}

**Important constraints:**
- DO NOT suggest songs I already have in my existing playlists
- Avoid explicit lyrics (clean versions only)
- Focus on discovering new/lesser-known artists, not just popular hits
- Provide 5-7 song recommendations maximum

**Workflow:**
- Add recommendations to my Spotify queue (not directly to playlists)
- I'll review and save the ones I like to appropriate playlists later

**For each recommendation, include:**
- Artist and song name
- Brief explanation (1-2 sentences) of why it fits my current mood/activity
- Similar artists I might also enjoy

Please help me discover music that matches this vibe while following these preferences.

Using it:

>> spotify-discover

Now you just fill in your current mood and activity, and get perfectly tailored recommendations that follow all your rules—no need to repeat your constraints every time.

🔄 Other Common Use Cases

📋 Work Ticket Management

Create prompts for JIRA/Linear ticket formatting with your team's specific requirements
Include standard fields, priority levels, acceptance criteria templates
Avoid repeating your company's ticket standards every time

📧 Email Templates

Customer support responses with your company's tone and required disclaimers
Follow-up sequences that match your communication style
Automated inclusion of signatures, links, and standard information

📝 Code Review Guidelines

Technical review checklists with your team's specific standards
Security considerations and performance criteria
Documentation requirements and testing expectations

The common thread: stop repeating yourself. If you find yourself giving the same detailed instructions to your LLM repeatedly, create a prompt for it.

🔍 Discovering Existing Prompts

You can search your prompt library:

Can you search my prompts for "productivity" or "task management"?

Or list all available prompts:

What prompts do I have available?

✏️ Manual Editing

Prompts are stored as simple markdown files in your PROMPT_STORAGE_PATH directory. You can also create and edit them directly with your favorite text editor:

Each prompt is saved as {id}.md in your prompts directory
Use {{variable_name}} syntax for template variables
Standard markdown formatting is supported
File changes are automatically picked up by the server

💡 Best Practices

Use descriptive IDs: Choose prompt IDs that clearly indicate their purpose (e.g., meeting-notes, code-review-checklist)
Include helpful variables: Use {{variable_name}} for dynamic content that changes each time you use the prompt
Organize by category: Consider using prefixes like task-, content-, analysis- to group related prompts