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.
@abhichandra21
基本信息
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
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"
}
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
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。
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.
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.
Google Gemini, Anthropic Claude, OpenAI, Groq, Alibaba Qwen, Zhipu GLM, and OpenRouter (optimized for `openrouter/auto`). Each requires its own API key.
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.
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.
Python 3.10+ and the `mcp` package (`pip install mcp`). The server connects to external LLM APIs; no local model is required.
Yes. Set `PROMPTHEUS_TELEMETRY_ENABLED=0` in your environment, or view a summary with `promptheus telemetry summary`. All data is stored locally.

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