promptforge-mcp-server

Stevekaplanai/promptforge-mcp-server

3.2

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PromptForge MCP Server 2.0.2 is an advanced AI prompt optimization server designed for sophisticated prompt engineering with ML-based domain detection, pattern management, and analytics.

PromptForge MCP Server 2.0.2 is a cutting-edge Model Context Protocol server that enhances AI prompt engineering through intelligent optimization techniques. It leverages machine learning for automatic domain detection, allowing it to tailor prompts to specific fields such as programming, CPA marketing, and AI automation. The server includes a robust pattern management system that enables users to create, update, and manage optimization patterns for various domains. Additionally, it features an analytics engine that tracks optimization performance and metrics, providing valuable insights into the effectiveness of prompt modifications. With a template system for common use cases and support for chain-of-thought reasoning, PromptForge MCP Server ensures that prompts are not only optimized for clarity and intent but also formatted appropriately for different output types like JSON, Markdown, and tables. The server is designed to learn from user feedback, continuously improving its optimization capabilities.

Features

  • ML-Based Domain Detection: Automatically detects the domain of prompts for tailored optimization.
  • Advanced Pattern Management: Allows creation and management of optimization patterns for different domains.
  • Analytics Engine: Tracks and analyzes optimization performance and metrics.
  • Template System: Provides pre-built templates for common use cases.
  • Feedback Learning: Learns from user feedback to enhance optimization processes.

Usages

local integration stdio

python
mcp.run(transport='stdio')  # Tools defined via @mcp.tool() decorator

remote integration sse

python
mcp.run(transport='sse', host="0.0.0.0", port=8000)  # Specify SSE endpoint

remote integration streamable http

yaml
paths:
  /mcp:
    post:
      x-ms-agentic-protocol: mcp-streamable-1.0  # Copilot Studio integration

platform integration github

{"command": "docker", "args": ["run", "-e", "GITHUB_PERSONAL_ACCESS_TOKEN", "ghcr.io/github/github-mcp-server"]}

platform integration atlassian

{
  "context": {
    "company": "Schapira CPA",
    "industry": "Tax and Accounting Services",
    "audience": "Mid-market owner-operated businesses",
    "tone": "professional"
  }
}

Tools

  1. optimize_prompt

    Analyzes and enhances prompts with intelligent optimization.

  2. manage_patterns

    Manage optimization patterns for different domains.

  3. track_analytics

    Track and query optimization analytics.