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Promptheus

@abhichandra21

代码仓库

关于 Promptheus

AI-powered prompt refinement tool with adaptive questioning and multi-provider support. Provides 5 MCP tools (refine_prompt, tweak_prompt, list_models, list_providers, validate_environment) for intelligent prompt engineering. Supports Google Gemini, Anthropic Claude, OpenAI, Groq

#prompt-engineering#ai#llm#mcp#multi-provider#gemini#claude#openai#groq#refinement#prompt-optimization

基本信息

分类

AI 与智能体

传输方式

stdio

发布者

abhichandra21

提交者

Abhishek Chandra

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "promptheus": {
      "type": "stdio",
      "command": "~/Promptheus/venv/bin/python",
      "args": [
        "-m",
        "promptheus.main",
        "mcp"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "API-KEY"
      }
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Promptheus?

Promptheus is a Model Context Protocol (MCP) server that analyzes, refines, and optimizes prompts for large language models. It integrates with multiple AI providers (Google, OpenAI, Anthropic, Groq, Qwen, etc.) and exposes its capabilities as standardized MCP tools for use by MCP-compatible clients.

How to use Promptheus?

Install with pip install promptheus and ensure at least one provider API key is set in a .env file or environment variables. Start the MCP server with promptheus mcp or python -m promptheus.mcp_server. The server provides tools such as refine_prompt, tweak_prompt, list_models, list_providers, and validate_environment. An interactive CLI mode (promptheus) and a web UI (promptheus web) are also available.

Key features of Promptheus

  • Adaptive task detection (refinement vs. direct optimization)
  • Multi-provider support (Google, OpenAI, Anthropic, Groq, Alibaba, Zhipu, OpenRouter)
  • Interactive refinement through natural conversation
  • Session history tracking and reuse
  • Structured clarification workflow with AskUserQuestion integration
  • CLI and web UI for prompt management
  • Telemetry and analytics (local, anonymous, can be disabled)

Use cases of Promptheus

  • Refine a vague prompt into a detailed, audience-aware request
  • Iteratively improve prompts through targeted clarification questions
  • Apply surgical modifications to existing prompts (e.g., “make it shorter”)
  • Discover and validate available models and provider configurations
  • Integrate prompt optimization into automated pipelines or MCP clients

FAQ from Promptheus

What providers are supported?

Google Gemini, Anthropic Claude, OpenAI, Groq, Alibaba Qwen, Zhipu GLM, and OpenRouter (optimized for openrouter/auto). Each requires its own API key.

How do I configure API keys?

Create a .env file with keys like GOOGLE_API_KEY=... or run promptheus auth for interactive setup. Use list_providers or validate_environment to check configuration.

What does the MCP server do exactly?

It exposes tools for prompt refinement (refine_prompt), prompt tweaking (tweak_prompt), model discovery (list_models), provider validation (list_providers), and environment testing (validate_environment). It supports a two‑phase workflow with optional clarification questions.

Are there any runtime dependencies?

Python 3.10+ and the mcp package (pip install mcp). The server connects to external LLM APIs; no local model is required.

Can I disable telemetry?

Yes. Set PROMPTHEUS_TELEMETRY_ENABLED=0 in your environment, or view a summary with promptheus telemetry summary. All data is stored locally.

评论

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