Prompt Decorators
A standardized framework for enhancing how LLMs process and respond to prompts through composable decorators, featuring an official open standard specification and Python reference implementation. Claude Code plugin and MCP server integration.
What is Prompt Decorators?
Prompt Decorators is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to standardized framework for enhancing how llms process and respond to prompts through composable decorators, featuring an official open standard specification and python reference implementation. claud...
A standardized framework for enhancing how LLMs process and respond to prompts through composable decorators, featuring an official open standard specification and Python reference implementation. Claude Code plugin and MCP server integration.
This server falls under the Developer Tools category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- A standardized framework for enhancing how LLMs process and
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx prompt-decoratorsConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Prompt Decorators
Prompt Decorators is a standardized open-source framework that lets developers annotate prompts with composable decorator syntax to control how LLMs reason, format, and respond. The framework ships with 140+ pre-built decorators covering reasoning depth, output formatting, step-by-step processing, and domain-specific behaviors, all backed by a formal specification and Python reference implementation. It integrates with Claude Code via a /decorate plugin command and exposes an MCP server so any compatible AI client can apply decorators programmatically.
Prerequisites
- Python 3.8+ with pip
- prompt-decorators package installed with MCP extras
- An MCP-compatible client such as Claude Desktop or Claude Code
- Optional: Claude Code CLI for the /decorate plugin integration
Install the prompt-decorators package with MCP support
Install the package from PyPI including the MCP integration extras needed to run the server.
pip install "prompt-decorators[mcp]"Verify the installation and decorator registry
Confirm the package is installed and the decorator registry loads without errors.
python -c "import prompt_decorators; print(prompt_decorators.__version__)"
python -m prompt_decorators verifyStart the MCP server
Launch the prompt-decorators MCP server in stdio mode for use with Claude Desktop or Claude Code.
python -m prompt_decorators.mcp_serverAdd the server to your MCP client configuration
Register the server in your claude_desktop_config.json so Claude Desktop can launch it automatically.
{
"mcpServers": {
"prompt-decorators": {
"command": "python",
"args": ["-m", "prompt_decorators.mcp_server"]
}
}
}Use decorators in Python code
Load decorator definitions and apply them to prompts programmatically to see how they transform the input before sending to an LLM.
import prompt_decorators as pd
pd.load_decorator_definitions()
reasoning = pd.create_decorator_instance("Reasoning", depth="comprehensive")
prompt = "Explain the tradeoffs between microservices and monoliths."
decorated = reasoning.apply(prompt)
print(decorated)Prompt Decorators Examples
Client configuration
Claude Desktop configuration to auto-launch the prompt-decorators MCP server.
{
"mcpServers": {
"prompt-decorators": {
"command": "python",
"args": ["-m", "prompt_decorators.mcp_server"]
}
}
}Prompts to try
Ask the AI to apply decorators or use decorated prompts directly once the server is running.
- "Apply the Reasoning decorator with depth=comprehensive to: explain how transformers work"
- "Use StepByStep formatting to walk me through setting up a PostgreSQL replication cluster"
- "List all available decorators in the registry and describe what each category does"
- "Apply OutputFormat(format=json) and Reasoning(depth=brief) together to analyze this dataset"Troubleshooting Prompt Decorators
MCP server module not found after installation
Ensure you installed with the mcp extra: pip install "prompt-decorators[mcp]". Without it, the mcp_server submodule may not be present.
Decorator registry is empty or verify command fails
Run pip install "prompt-decorators[all]" to get all optional dependencies, then re-run python -m prompt_decorators verify to see detailed registry status.
Decorated prompts are not behaving as expected with the LLM
Some decorators prepend instruction text to the prompt. Print the decorated prompt before sending to verify the transformation looks correct. Check the decorator's parameter defaults using the registry metadata.
Frequently Asked Questions about Prompt Decorators
What is Prompt Decorators?
Prompt Decorators is a Model Context Protocol (MCP) server that standardized framework for enhancing how llms process and respond to prompts through composable decorators, featuring an official open standard specification and python reference implementation. claude code plugin and mcp server integration. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Prompt Decorators?
Follow the installation instructions on the Prompt Decorators GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Prompt Decorators?
Prompt Decorators works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Prompt Decorators free to use?
Yes, Prompt Decorators is open source and available under the Apache-2.0 license. You can use it freely in both personal and commercial projects.
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Set Up Prompt Decorators in Your Editor
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Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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