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Promptheus MCP Server

@abhichandra21

Repository

Basic information

Category

AI & Agents

Transports

stdio

Author

abhichandra21

Submitted by

Abhishek Chandra

About Promptheus MCP Server

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

Promptheus MCP Server config

Add this server to your MCP-compatible client using the configuration below.

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

Promptheus MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

Frequently asked questions

1

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.

2

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.

3

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.

4

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.

5

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.

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