Trino MCP Server

Trino MCP Server in Go

The Trino MCP Server bridges the gap between AI assistants and Trino’s distributed SQL engine, allowing conversational agents to run analytics queries directly against large, heterogeneous data lakes and warehouses. By exposing Trino’s capabilities through the Model Context Protocol (MCP), developers can integrate powerful, real‑time data insights into their AI workflows without embedding database drivers or writing custom connectors.

Problem Solved

In many data‑centric applications, AI assistants need to answer questions that depend on up‑to‑date analytics. Traditional approaches require the assistant to maintain its own database connection, handle authentication, and translate natural language into SQL—a complex, error‑prone process. The Trino MCP Server abstracts these concerns behind a simple, standardized interface. It manages transport (HTTP or STDIO), optional OAuth 2.0 authentication, and query execution while providing a consistent set of tools that AI clients can invoke.

What the Server Does

The server offers a suite of MCP tools that mirror Trino’s native operations: executing arbitrary queries, listing available catalogs, schemas, and tables, retrieving table schemas, and explaining query plans. When an AI assistant calls , the server forwards the SQL to Trino, streams results back in a structured format, and handles any necessary authentication tokens. The same mechanism supports discovery tools (, , etc.), enabling assistants to auto‑populate dropdowns or suggest available datasets.

Key Features

• High performance Go implementation: Lightweight, low‑latency service suitable for production deployments.
• Dual transport support: Works over HTTP for web‑based clients and STDIO for local or embedded tools.
• Optional OAuth 2.0 integration: Seamlessly authenticate with providers such as Okta, Google, or Azure AD.
• Docker‑ready: Easy to spin up in containerized environments for CI/CD or cloud deployment.
• Extensible catalog support: Trino’s connector ecosystem (PostgreSQL, MySQL, S3/Hive, BigQuery, MongoDB) is fully exposed via the MCP interface.

Real‑World Use Cases

• Data‑driven chatbots: A customer support bot can query sales data on the fly, answering “What were our quarterly earnings?” without pre‑loading metrics.
• Business intelligence assistants: Analysts can ask natural language questions that are translated into optimized Trino queries, receiving results instantly within the AI tool.
• Data discovery platforms: Internal tools can use commands to populate schema browsers, making data exploration effortless for non‑technical users.

Integration with AI Workflows

MCP clients such as Claude Code, Claude Desktop, or custom agents can import the Trino MCP Server’s tool definitions automatically. Once registered, an assistant can invoke as a first‑class action, receiving structured JSON results that can be passed to subsequent prompts or visualizations. The server’s authentication middleware ensures that only authorized users access sensitive datasets, while the transport flexibility allows deployment in both cloud and on‑premises environments.

Standout Advantages

Unlike generic JDBC or ODBC connectors, the Trino MCP Server delivers a standardized, protocol‑agnostic interface that fits naturally into modern AI assistant architectures. Its Go implementation guarantees minimal overhead, and the built‑in OAuth support aligns with enterprise security practices. By exposing Trino’s distributed query engine through MCP, developers gain a powerful, secure, and easy‑to‑use data layer that can be integrated into conversational AI systems with minimal friction.