Connects AI models to Steampipe, enabling them to execute queries and retrieve data.
This Python-based tool acts as a bridge between AI models and the Steampipe CLI, allowing AI to query and interact with various data sources through Steampipe's plugins. It leverages the Model Context Protocol (MCP) to facilitate communication between the AI model and Steampipe, enabling the execution of SQL queries and retrieval of structured data. It includes an MCP Inspector for testing and troubleshooting.
Key Features
01Provides a Python-based server implementation
02Enables AI models to execute Steampipe queries
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04Utilizes the Model Context Protocol (MCP) for communication
05Includes MCP Inspector for testing and debugging
06Supports any LLM with MCP capabilities
Use Cases
01Allowing AI agents to gather information from cloud infrastructure
02Enabling AI to query and analyze code repositories
03Integrating data from various Steampipe plugins into AI workflows