sl-bigquery-mcp is an open-source Python package that implements a Model Context Protocol (MCP) server for accessing Google BigQuery. Below are 6 infrastructure & backend apps with similar functionality to sl-bigquery-mcp, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
sql-query-mcp is an open-source, read-only SQL MCP server supporting PostgreSQL and MySQL. It allows developers to query databases using the MCP protocol from the command line, facilitating integration with other MCP-compatible tools.
A production-ready MCP server that exposes PostgreSQL databases via the Model Context Protocol
sql-sop-mcp is an open-source Model Context Protocol server that exposes the sql-sop SQL linter to large language models via API. It enables developers to integrate SQL safety checks into LLM-powered workflows, supporting tools like Claude, Cursor, and ChatGPT.
dbt-mcp is an open-source Model Context Protocol (MCP) server that enables interaction with dbt resources for analytics and AI agent workflows. It is designed for data engineers and developers building data pipelines and analytics solutions.
plesk-mcp is an open-source MCP server that facilitates automation and orchestration of model context protocol workflows, particularly for hosting and AI infrastructure scenarios. It is designed for engineers integrating AI models into hosting platforms.
msmcp-azure is an open-source server for Azure that implements the Model Context Protocol (MCP), enabling structured management and orchestration of AI model contexts. It is designed for AI infrastructure engineers deploying and managing models on Azure.
