analyze_promptLABSCO SUMMARY
A strategy menu with a selection guide attached.
The useful part is not that it can rewrite a prompt — it is that the strategies are named, documented and matched to prompt types, so "complex problem" points at tree_of_thoughts and "classification" at medprompt. Treat the improvement percentages in the README as the published research figures they are cited as, not as measurements of your prompt. Nothing here calls a model on your behalf, so there is no key to supply and no per-call cost.
What it is
A prompt-engineering server. It analyses a prompt, applies a chosen optimisation strategy or selects one automatically, and hands back production-ready templates for common professional tasks.
What you get
- analyze_prompt reports on a prompt's quality and names the issues it finds
- optimize_prompt applies a specific strategy — clarity, specificity, chain of thought, few-shot, structured output or role-based
- auto_optimize picks the strategy for you when you do not want to choose
- advanced_optimize applies the research-backed set: tree of thoughts, constitutional AI, automatic prompt engineer, meta-prompting, self-refine, TEXTGRAD, medprompt and PromptWizard
- get_prompt_template returns a basic template; get_domain_template returns a professional one and list_domain_templates browses what is available
- Templates cover eleven domains, including business analysis, product management, content creation, development, communication, strategy, operations, legal, customer experience, data analysis and meeting management
Requirements
Python 3.8 or higher. Clone the repository, install from requirements.txt, and point the client at prompt_optimizer.py — the setup script setup_interactive.py writes the Claude Desktop configuration for you. No API key and no account; MCP_LOG_LEVEL set to debug turns on verbose logging.
Setup effort
Build from source — git clone https://github.com/Bubobot-Team/mcp-prompt-optimizer
USE CASES
01
Working out why a prompt underperforms
Analysis names the issues instead of just returning a rewrite.
02
Improving a prompt without picking a technique
Auto-selection chooses the strategy and applies it.
03
Applying a specific technique on purpose
Strategies are named and selectable, with a table matching prompt types to techniques.
04
Starting from something proven
Domain templates cover the recurring professional tasks across eleven areas.
7 tools
Listed in project docs. Your client may show a different list.
optimize_promptauto_optimizeget_prompt_templateadvanced_optimizeget_domain_templatelist_domain_templatesBEFORE YOU INSTALL
What to know first
Tools you get
7 tools named in the project's documentation.
Where it runs
The documented client runs the server on your machine.
INSTALLATION
Connect your client
Server setup
TERMINAL
git clone https://github.com/Bubobot-Team/mcp-prompt-optimizer
cd mcp-prompt-optimizer
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txtMCP Clients
Claude Desktop
CLAUDE DESKTOP · JSON
{
"mcpServers": {
"prompt-optimizer": {
"command": "<YOUR_PATH_TO_MCP_PROMPT_OPTIMIZER>/venv/bin/python3",
"args": [
"<YOUR_PATH_TO_MCP_PROMPT_OPTIMIZER>/prompt_optimizer.py"
],
"env": {}
}
}
}<YOUR_PATH_TO_MCP_PROMPT_OPTIMIZER> is the absolute path of your clone in both places. The command is the Python inside the venv the steps above create, so the server sees the packages pip installed there; on Windows it is venv\Scripts\python.exe.
