Unlock the power of AI-driven security and compliance analysis with
Powerpipe MCP bridges AI assistants and your compliance data, allowing natural language:
- Exploration of security benchmarks and compliance frameworks
- Analysis of compliance status and findings
- Development and customization of controls
- Remediation guidance for failed checks
Works with your local
Node.js v16 or higher (includes npx
)Powerpipe installed and configured - A directory containing your Powerpipe mod files (required)
Add Powerpipe MCP to your AI assistant's configuration file:
{
"mcpServers": {
"powerpipe": {
"command": "npx",
"args": [
"-y",
"@turbot/powerpipe-mcp",
"/path/to/your/mod/is/required"
]
}
}
}
The mod location argument is required and must point to a directory containing your Powerpipe mod files. This is where Powerpipe will look for benchmarks, controls, and other resources.
Assistant | Config File Location | Setup Guide |
---|---|---|
Claude Desktop | claude_desktop_config.json |
|
Cursor | ~/.cursor/mcp.json |
Save the configuration file and restart your AI assistant for the changes to take effect.
Here are some example questions you can ask to interact with your Powerpipe installation:
Explore available compliance frameworks:
What Powerpipe benchmarks do we have available?
Simple, specific questions work well:
Show me all controls related to S3 bucket encryption in the CIS AWS benchmark
Generate a compliance report:
What's our current compliance status for the NIST controls?
Dive into the details:
Find all failed controls in the AWS Security benchmark and explain why they failed
Get information about specific requirements:
Show me all controls related to password policies across our benchmarks
Explore with wide ranging questions:
Analyze our compliance gaps and suggest remediation steps
Remember to:
- Be specific about which benchmarks or frameworks you're interested in
- Mention the type of controls you want to analyze (encryption, access, networking, etc.)
- Start with simple queries before adding complex conditions
- Use natural language - the LLM will handle finding the right controls and benchmarks
- Be bold and open, it's amazing what insights the LLM will discover!
The Powerpipe MCP server includes a set of prompts that can be used to guide AI assistants in working with Powerpipe.
- powerpipe_mod_location
- Critical first step: Sets up the working directory for your Powerpipe mods
- Must be configured before using any other tools
- Get or set the directory containing your Powerpipe mod files
- powerpipe_benchmark_list, powerpipe_benchmark_show, powerpipe_benchmark_run
- Discover and work with complete compliance frameworks
- List available compliance benchmarks and understand their scope
- View detailed benchmark information including controls, tags, and documentation
- Execute benchmarks to evaluate infrastructure against framework requirements
- powerpipe_control_list, powerpipe_control_show, powerpipe_control_run
- Work with individual compliance requirements
- List and examine specific controls from various frameworks
- View control implementation details and associated queries
- Run individual controls for targeted compliance checks
- powerpipe_detection_list, powerpipe_detection_show, powerpipe_detection_run
- Identify specific security issues and compliance violations
- List available security detections
- View detection details including severity and remediation guidance
- Run targeted security checks with actionable results
- powerpipe_query_list, powerpipe_query_show
- Examine the foundation of compliance evaluation
- List all SQL queries that power controls and detections
- View query implementations to understand compliance checks
- Analyze how infrastructure data is evaluated
- powerpipe_dashboard_list, powerpipe_dashboard_show, powerpipe_dashboard_run
- Work with compliance and security visualizations
- List available dashboards for compliance insights
- View dashboard structure and components
- Execute dashboards to get JSON snapshot data of compliance status
- powerpipe_variable_list, powerpipe_variable_show
- Customize compliance evaluations
- List available configuration variables
- View variable details and current settings
- Understand how to customize checks for your environment
- powerpipe_docs_hcl
- Essential reference for Powerpipe development
- Access detailed HCL documentation and examples
- Understand syntax for all Powerpipe elements
- Get guidance for writing and modifying mod files
The Powerpipe MCP provides access to the following resources:
- status
- Represents the current state of the Powerpipe server
- Properties include:
- powerpipe_version: The current Powerpipe CLI version
- server_version: The MCP server version
- server_start_time: When the server was started
- mod_location: Current working directory for mods
This resource enables AI tools to check and verify the Powerpipe environment state.
- Clone the repository and navigate to the directory:
git clone https://github.com/turbot/powerpipe-mcp.git
cd powerpipe-mcp
- Install dependencies:
npm install
- Build the project:
npm run build
To test your local development build with AI tools that support MCP, update your MCP configuration to use the local dist/index.js
instead of the npm package. For example:
{
"mcpServers": {
"powerpipe": {
"command": "node",
"args": [
"/absolute/path/to/powerpipe-mcp/dist/index.js",
"/path/to/your/mod/is/required"
]
}
}
}
Or, use the MCP Inspector to validate the server implementation:
npx @modelcontextprotocol/inspector dist/index.js
The following environment variables can be used to configure the MCP server:
POWERPIPE_MCP_MOD_LOCATION
: Set the working directory for Powerpipe mods (falls back to POWERPIPE_MOD_LOCATION if not set)POWERPIPE_MCP_LOG_LEVEL
: Control MCP server logging verbosity with these values:- ERROR
- WARN
- INFO
- DEBUG
- TRACE
POWERPIPE_MCP_MEMORY_MAX_MB
: Maximum memory buffer size in megabytes (default: 100)
This repository is published under the
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