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Trino MCP Server

@stinkgen

リポジトリ

基本情報

カテゴリ

その他

ライセンス

MIT

トランスポート

stdio

作者

stinkgen

Trino MCP Server について

MCP Server for Trino

#trino#mcp#sql-query#ai-integration

Trino MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "trino_mcp": {
      "command": "python",
      "args": [
        "llm_trino_api.py"
      ]
    }
  }
}

Trino MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Trino MCP Server?

A Model Context Protocol server for Trino, providing AI models with structured access to Trino's distributed SQL query engine. It is currently a beta release (v0.1.2).

How to use Trino MCP Server?

Start the server with docker-compose up -d. Verify the API at http://localhost:9097/api/query. For a non-containerized version, run python llm_trino_api.py on port 8008. Use STDIO transport (recommended) inside the container; client scripts run on the local machine and connect via docker exec.

Key features of Trino MCP Server

  • Exposes Trino resources through the MCP protocol
  • Enables AI tools to query and analyze Trino data
  • Provides STDIO transport (reliable) and SSE transport (not recommended)
  • Offers both Docker container API and standalone Python API
  • Includes demo scripts for generating and querying test data
  • Fixed catalog handling and Docker container initialization issues

Use cases of Trino MCP Server

  • Let LLMs query Trino databases via natural language prompts
  • Run complex analytical SQL queries through AI assistants
  • Get database schema information programmatically
  • Analyze data and present results with visualizations (e.g., Mermaid charts)

よくある質問

1

Which transport should I use?

STDIO transport works reliably. SSE transport has critical issues with MCP 1.3.0 and causes server crashes on client disconnection; avoid its use until a newer MCP version is integrated.

2

What are the runtime requirements?

Docker and docker-compose for the containerized version; Python for the standalone API. All scripts can run on the local machine and communicate with Docker containers via `docker exec`.

3

Where does the demo data live?

The demo data is generated by `tools/create_bullshit_data.py` and loaded into Trino's memory catalog using `load_bullshit_data.py`. The default catalog is `memory`.

4

How do I run tests?

Use `python test_mcp_stdio.py` for STDIO transport testing, or `./run_tests.sh` for automated tests. The `test_bullshit_query.py` script demonstrates complex queries through MCP.

5

Are there known limitations?

Yes. The SSE transport is broken in MCP 1.3.0. The Docker container API previously had a 503 initialization issue (now fixed). The project is in beta (v0.1.2) and may have other edge cases.

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