refine_promptLABSCO SUMMARY
It asks before it rewrites.
The clarification contract is the interesting part: instead of guessing your audience and tone, the server hands back structured questions with IDs, your client asks you, and the answers come back mapped. That makes the refined prompt reproducible rather than a one-off improvisation — and the same flow degrades gracefully in clients that cannot ask questions.
What it is
Promptheus refines prompts for LLMs, and ships an MCP server so the refinement happens inside your client. It detects whether a task needs clarification or direct optimisation, asks targeted questions when it needs them, and returns a prompt you can run.
What you get
refine_prompt— refinement with an optional clarification round; it either returns the refined prompt or a set of questions plus ananswer_mapping, which you answer through your client's own question tool and send backtweak_prompt— a surgical edit to an existing prompt from a description such as "make it shorter"list_modelsandlist_providers— which providers are configured and which models they exposevalidate_environment— checks configuration and, optionally, real API connectivity per provider- Provider and model can be overridden per call, so one prompt can be refined by whichever model you prefer
Requirements
Python 3.10 or higher. pip install promptheus, then start the server with promptheus mcp (or python -m promptheus.mcp_server). At least one provider key is needed — GOOGLE_API_KEY, ANTHROPIC_API_KEY, OPENAI_API_KEY, GROQ_API_KEY, QWEN_API_KEY or GLM_API_KEY — with PROMPTHEUS_PROVIDER and PROMPTHEUS_MODEL available to pin the choice. The mcp package must be installed. Package version 0.3.2; the registry entry publishes 0.3.1 over stdio.
Setup effort
Follow the published steps — pip install promptheus
USE CASES
Turning a one-line request into a brief
Send the rough prompt, answer the questions it comes back with, and get a prompt that states audience, tone and scope.
Adjusting a prompt that almost works
Describe the change you want rather than rewriting it by hand, and get the modified prompt back.
Finding out why a provider is not responding
Check which providers are configured, then test real connectivity before blaming the prompt.
Refining with a different model than you chat with
Override provider and model on the call so the refinement runs on the model you trust for that job.
5 tools
Listed in project docs. Your client may show a different list.
tweak_promptlist_modelslist_providersvalidate_environmentBEFORE YOU INSTALL
What to know first
Tools you get
5 tools named in the project's documentation.
Requires
- pip on PATH
- Python 3.10+
- At least one provider API key in your environment: GOOGLE_API_KEY, ANTHROPIC_API_KEY, OPENAI_API_KEY, GROQ_API_KEY, QWEN_API_KEY or GLM_API_KEY
INSTALLATION
Connect your client
Server setup
pip install promptheusCreate a .env file with at least one provider API key (for example GOOGLE_API_KEY=<YOUR_GOOGLE_API_KEY>), or run promptheus auth for the interactive setup
Add Promptheus to your MCP client as a local (stdio) server whose command is promptheus mcp (or python -m promptheus.mcp_server). The project publishes no client configuration, so write the entry in your client's own format
If the server reports that the mcp package is not installed, run pip install mcp