Model Context Protocol (MCP) Server for Trino
This MCP server implementation in Go allows AI assistants to seamlessly communicate with Trino's distributed SQL engine. It supports catalog, schema, and table discovery, executes complex SQL queries, and provides integration options via Docker, HTTP, and SSE transports. Designed for high performance, it facilitates AI-driven data exploration and analysis on large datasets efficiently.
Added on:
Created by:
Apr 28 2025
This MCP server implementation in Go allows AI assistants to seamlessly communicate with Trino's distributed SQL engine. It supports catalog, schema, and table discovery, executes complex SQL queries, and provides integration options via Docker, HTTP, and SSE transports. Designed for high performance, it facilitates AI-driven data exploration and analysis on large datasets efficiently.
Added on:
Created by:
Apr 28 2025
Tommy Nguyen
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What is Model Context Protocol (MCP) Server for Trino?
The MCP server for Trino provides a robust, high-performance platform enabling AI assistants and clients to access and query Trino's distributed SQL engine through the Model Context Protocol. Implemented in Go, it supports features such as catalog, schema, and table discovery, execution of complex SQL queries, and data structure retrieval. It offers flexible connection options including Docker container support, HTTP transport with Server-Sent Events, and standard MCP tools. The server ensures secure, efficient, and standardized interactions with Trino, facilitating large-scale data analytics, exploration, and integration of AI workflows with minimal configuration and high scalability.
Who will use Model Context Protocol (MCP) Server for Trino?
- AI Assistants
- Data Analysts
- Data Engineers
- Business Intelligence Tools
- Developers integrating Trino with AI applications
How to use the Model Context Protocol (MCP) Server for Trino?
- Step 1: Install the MCP server via Docker, binary download, or from source.
- Step 2: Configure environment variables with Trino connection details.
- Step 3: Start the server using Docker, HTTP, or command-line options.
- Step 4: Connect your AI application or tool to the MCP server via supported transport protocols.
- Step 5: Use MCP tools like execute_query, list_catalogs, list_schemas, list_tables, or get_table_schema to interact with Trino datasets.
Model Context Protocol (MCP) Server for Trino's Core Features & Benefits
The Core Features
- execute_query
- list_catalogs
- list_schemas
- list_tables
- get_table_schema
The Benefits
- Standardized API for AI applications to interact with Trino
- Supports high-performance distributed SQL querying
- Flexible deployment via Docker and HTTP SSE
- Catalog and schema discovery for efficient data navigation
- Secure and scalable integration for large datasets
Model Context Protocol (MCP) Server for Trino's Main Use Cases & Applications
- AI-enabled data exploration and analytics on large datasets using Trino
- Automated querying and discovery of databases, schemas, and tables for data engineers
- Integration of Trino with various AI tools and assistants for seamless data workflows
FAQs of Model Context Protocol (MCP) Server for Trino
Developer
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