# Trino

> Use this tool when you need to integrate large language models with Trino databases, enabling AI-driven data analysis and natural language querying of data warehouses. It provides a REST interface for executing SQL queries and supports features like query explanation and custom catalogs. Ideal for use cases requiring AI assistants to interact with Trino-managed data, it accepts SQL queries as input and returns formatted result outputs.

Canonical page: https://skillsregistry.net/skills/stinkgen-trino  
JSON: https://api.skillsregistry.net/v1/skills/stinkgen-trino

## Description

This MCP server implementation provides a bridge between large language models (LLMs) and Trino databases. Developed by the Trino MCP Team, it offers a FastAPI-based REST interface for executing SQL queries against Trino via the Model Context Protocol. The server supports features like query explanation, custom catalogs and schemas, and formatted result output. It's designed for use cases requiring AI assistants to interact with Trino-managed data, such as natural language querying of data warehouses or AI-driven data analysis.

## Trust

- **Trust score (0–1):** 0.71
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/stinkgen-trino)
- **Repository:** <https://github.com/stinkgen/trino_mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "stinkgen-trino"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/stinkgen-trino` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/stinkgen-trino/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt