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MCP Prompt Optimizer Server
- python
20
GitHub Stars
python
Language
4 months ago
First Indexed
2 months ago
Catalog Refreshed
Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"bubobot-team-mcp-prompt-optimizer": {
"command": "python3",
"args": [
"/path/to/mcp-prompt-optimizer/prompt_optimizer.py"
]
}
}
}You can run the MCP Prompt Optimizer as a dedicated server that enhances your prompts with research-backed optimization strategies and ready-to-use domain templates. It helps you get clearer, more actionable prompts, apply advanced reasoning patterns, and reuse production-ready templates across common domains.
How to use
You connect to the MCP Prompt Optimizer using an MCP client that supports standard server configurations. Start by choosing the optimization path that fits your task, then issue prompts to analyze quality, apply targeted optimization, or auto-select the best strategy for your needs. You can request domain templates to accelerate consistent work across projects, and you can combine multiple strategies for complex problems.
How to install
Prerequisites: you need Python installed on your system. You will also run a local setup to prepare the MCP server for use.
Quick setup
# Clone the repository
git clone <repository-url>
cd mcp-prompt-optimizer
# Create virtual environment (recommended)
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install dependencies
./install.sh
# Or install manually
pip install -r requirements.txt
# Configure Claude Desktop
python3 setup_interactive.py
Manual configuration
Add to your Claude Desktop configuration file. This example uses the macOS path; adjust for Windows or Linux as needed.
{
"mcpServers": {
"prompt-optimizer": {
"command": "python3",
"args": ["/path/to/mcp-prompt-optimizer/prompt_optimizer.py"],
"env": {}
}
}
}
Available tools
analyze_prompt
Analyzes prompt quality and identifies issues to improve clarity and effectiveness.
optimize_prompt
Applies specified optimization strategies to enhance prompt performance.
auto_optimize
Automatically selects the most suitable optimization strategy for a given task.
get_prompt_template
Returns basic templates to guide prompt construction.
advanced_optimize
Applies research-backed, advanced optimization strategies for complex tasks.
get_domain_template
Provides professional domain templates for structured outputs.
list_domain_templates
Lists all available domain templates by category.