Steampipe Model Context Protocol (MCP) Server

by turbot

44 stars
274 downloads
Not rated
GitHub

About

Enable AI assistants to explore and query your Steampipe data!

Details

Author
turbot
GitHub stars
44
Downloads
274
Categories
Other, AI

- Query cloud and security logs using SQL (PostgreSQL syntax).
- List, filter, and inspect available Steampipe tables.
- List and show details of installed Steampipe plugins.
- Connect to local Steampipe or Turbot Pipes workspaces.
- Provides a best_practices prompt to optimize LLM responses.
- Exposes a status resource to verify connection state.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

  1. Download and install Highlight from highlightai.com/download
  2. Navigate to the plugins tab and select "Add Custom Plugin"
  3. Configure the plugin with the settings below
    Plugin Name Steampipe Model Context Protocol (MCP) Server
    Command (node, npx, python, etc.)

    Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.

  4. Enable "Start Automatically" if you want the plugin to start when Highlight launches

From the repository

Install Node.js v16 or higher and have Steampipe running locally (steampipe service start) or a Turbot Pipes workspace. Add the server configuration to your AI assistant’s MCP config file (e.g., claude_desktop_config.json for Claude Desktop, ~/.cursor/mcp.json for Cursor). After restarting the assistant, run the best_practices prompt to teach the LLM how to work with Steampipe, then ask natural‑language questions about your infrastructure.

steampipe_query

Query cloud infrastructure, SaaS, APIs, code and more with SQL. Queries are read-only and must use PostgreSQL syntax. For best performance: limit columns requested, use materialized CTEs instead of joins. Trust the search path unless sure you need to specify a schema. Check available tables and columns before querying using steampipe_table_list and steampipe_table_show.

steampipe_table_list

List all available Steampipe tables. Use schema and filter parameters to narrow down results.

steampipe_table_show

Get detailed information about a specific Steampipe table, including column definitions, data types, and descriptions.

steampipe_plugin_list

List all Steampipe plugins installed on the system. Plugins provide access to different data sources like AWS, GCP, or Azure.

steampipe_plugin_show

Get details for a specific Steampipe plugin installation, including version, memory limits, and configuration.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "steampipe model context protocol (mcp) server": {
            "steampipe": {
                "command": "npx",
                "args": [
                    "-y",
                    "@turbot/steampipe-mcp"
                ]
            }
        }
    }
}

McpServers

{
    "steampipe": {
        "command": "npx",
        "args": [
            "-y",
            "@turbot/steampipe-mcp"
        ]
    }
}

Steampipe Model Context Protocol (MCP) Server

Unlock the power of AI-driven infrastructure analysis with Steampipe! This Model Context Protocol server seamlessly connects AI assistants like Claude to your cloud infrastructure data, enabling natural language exploration and analysis of your entire cloud estate.

Steampipe MCP bridges AI assistants and your infrastructure data, allowing natural language:
- Queries across AWS, Azure, GCP and 100+ cloud services
- Security and compliance analysis
- Cost and resource optimization
- Query development assistance

Works with both local Steampipe installations and Turbot Pipes workspaces, providing safe, read-only access to all your cloud and SaaS data.

Installation

Prerequisites

- Node.js v16 or higher (includes npx)
- For local use: Steampipe installed and running (steampipe service start)
- For Turbot Pipes: A Turbot Pipes workspace and connection string

Configuration

Add Steampipe MCP to your AI assistant's configuration file:

{
  "mcpServers": {
    "steampipe": {
      "command": "npx",
      "args": [
        "-y",
        "@turbot/steampipe-mcp"
      ]
    }
  }
}

By default, this connects to your local Steampipe installation at postgresql://steampipe@localhost:9193/steampipe. Make sure to run steampipe service start first.

To connect to a Turbot Pipes workspace instead, add your connection string to the args:

{
  "mcpServers": {
    "steampipe": {
      "command": "npx",
      "args": [
        "-y",
        "@turbot/steampipe-mcp",
        "postgresql://my_name:my_pw@workspace-name.usea1.db.pipes.turbot.com:9193/abc123"
      ]
    }
  }
}

AI Assistant Setup

| Assistant | Config File Location | Setup Guide |
|-----------|---------------------|-------------|
| Claude Desktop | claude_desktop_config.json | Claude Desktop MCP Guide → |
| Cursor | ~/.cursor/mcp.json | Cursor MCP Guide → |

Save the configuration file and restart your AI assistant for the changes to take effect.

Prompting Guide

First, run the best_practices prompt included in the MCP server to teach your LLM how best to work with Steampipe. Then, ask anything!

Explore your cloud infrastructure:

What AWS accounts can you see?

Simple, specific questions work well:

Show me all S3 buckets that were created in the last week

Generate infrastructure reports:

List my EC2 instances with their attached EBS volumes

Dive into security analysis:

Find any IAM users with access keys that haven't been rotated in the last 90 days

Get compliance insights:

Show me all EC2 instances that don't comply with our tagging standards

Explore potential risks:

Analyze my S3 buckets for security risks including public access, logging, and encryption

Remember to:
- Be specific about which cloud resources you want to analyze (EC2, S3, IAM, etc.)
- Mention regions or accounts if you're interested in specific ones
- Start with simple queries before adding complex conditions
- Use natural language - the LLM will handle the SQL translation
- Be bold and exploratory - the LLM can help you discover insights across your entire infrastructure!

Capabilities

Tools

- steampipe_query
- Query cloud and security logs with SQL.
- For best performance: use CTEs instead of joins, limit columns requested.
- All queries are read-only and use PostgreSQL syntax.
- Input: sql (string): The SQL query to execute using PostgreSQL syntax

- steampipe_table_list
- List all available Steampipe tables.
- Optional input: schema (string): Filter tables by specific schema
- Optional input: filter (string): Filter tables by ILIKE pattern (e.g. '%ec2%')

- steampipe_table_show
- Get detailed information about a specific table, including column definitions, data types, and descriptions.
- Input: name (string): The name of the table to show details for (can be schema qualified e.g. 'aws_account' or 'aws.aws_account')
- Optional input: schema (string): The schema containing the table

- steampipe_plugin_list
- List all Steampipe plugins installed on the system. Plugins provide access to different data sources like AWS, GCP, or Azure.
- No input parameters required

- steampipe_plugin_show
- Get details for a specific Steampipe plugin installation, including version, memory limits, and configuration.
- Input: name (string): Name of the plugin to show details for

Prompts

- best_practices
- Best practices for working with Steampipe data
- Provides detailed guidance on:
- Response style and formatting conventions
- Using CTEs (WITH clauses) vs joins
- SQL syntax and style conventions
- Column selection and optimization
- Schema exploration and understanding
- Query structure and organization
- Performance considerations and caching
- Error handling and troubleshooting

Resources

- status
- Represents the current state of the Steampipe connection
- Properties include:
- connection_string: The current database connection string
- status: The connection state (connected/disconnected)

This resource enables AI tools to check and verify the connection status to your Steampipe instance.

Development

Clone and Setup

1. Clone the repository and navigate to the directory:

git clone https://github.com/turbot/steampipe-mcp.git
cd steampipe-mcp

2. Install dependencies:

npm install

3. Build the project:

npm run build

Testing

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": {
    "steampipe": {
      "command": "node",
      "args": [
        "/absolute/path/to/steampipe-mcp/dist/index.js",
        "postgresql://steampipe@localhost:9193/steampipe"
      ]
    }
  }
}

Or, use the MCP Inspector to validate the server implementation:

npx @modelcontextprotocol/inspector dist/index.js

Environment Variables

The following environment variables can be used to configure the MCP server:

- STEAMPIPE_MCP_LOG_LEVEL: Control server logging verbosity (default: info)
- STEAMPIPE_MCP_WORKSPACE_DATABASE: Override the default Steampipe connection string (default: postgresql://steampipe@localhost:9193/steampipe)

Open Source & Contributing

This repository is published under the Apache 2.0 license. Please see our code of conduct. We look forward to collaborating with you!

Steampipe is a product produced from this open source software, exclusively by Turbot HQ, Inc. It is distributed under our commercial terms. Others are allowed to make their own distribution of the software, but they cannot use any of the Turbot trademarks, cloud services, etc. You can learn more in our Open Source FAQ.

Get Involved

Join #steampipe on Slack →

Want to help but don't know where to start? Pick up one of the help wanted issues:
Steampipe
Steampipe MCP

No reviews yet — be the first

Sign in to leave a review

Use Google, GitHub, or an email account so ratings stay tied to real people.

Email sign in

No reviews posted yet.