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Keboola MCP Server

@keboola

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

keboola

Keboola MCP Server について

Model Context Protocol (MCP) Server for the Keboola Platform

Keboola 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": {
    "keboola-mcp-server": {
      "command": "uvx",
      "args": [
        "keboola_mcp_server",
        "--transport",
        "streamable-http"
      ]
    }
  }
}

Keboola 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。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is Keboola MCP Server?

Keboola MCP Server is an open-source bridge that connects your Keboola project to AI agents and MCP clients such as Cursor, Claude, Windsurf, and VS Code. It exposes Keboola features—storage access, SQL transformations, job triggers, and more—as callable tools for AI assistants, eliminating the need for glue code.

How to use Keboola MCP Server?

The easiest way is to use the remotely hosted server: navigate to Keboola Project Settings → MCP Server, copy the server URL (e.g., https://mcp.<YOUR_REGION>.keboola.com/mcp), and paste it into your AI assistant’s MCP settings. For local setup, clone the repository, set environment variables (KBC_STORAGE_TOKEN, KBC_STORAGE_API_URL, KBC_WORKSPACE_SCHEMA, optionally KBC_BRANCH_ID), install dependencies with uv, and start the server with a transport option (stdio or streamable-http).

Key features of Keboola MCP Server

  • Query tables and manage table or bucket descriptions (Storage)
  • Create, list, and inspect extractors, writers, data apps, and transformation configurations (Components)
  • Create SQL transformations using natural language
  • Run components and transformations, retrieve job execution details (Jobs)
  • Build and manage workflow pipelines with Conditional and Orchestrator Flows
  • Create, deploy, and manage Streamlit Data Apps over storage data
  • Search, read, and update project documentation and metadata via natural language
  • Work safely in development branches isolated from production

Use cases of Keboola MCP Server

  • AI agents querying Keboola storage tables directly from a chatbot
  • Generating SQL transformations from natural language prompts
  • Automating job runs and monitoring execution from an AI assistant
  • Building and orchestrating complex data pipelines without manual configuration
  • Managing project metadata and documentation interactively

よくある質問

1

What is the Remote MCP Server?

It is a hosted version of the server available on every multi-tenant Keboola stack. It supports OAuth authentication and eliminates the need for local setup.

2

How do I authenticate when using Keboola MCP Server?

For the remote server, authentication is done via OAuth: a browser window prompts you to log in with your Keboola account and select your project. For local setup, you provide a Storage API token (master or custom) via the `KBC_STORAGE_TOKEN` environment variable.

3

What are the requirements for local setup?

Python 3.10+ and `uv` are required. You also need access to a Keboola project with admin rights and a valid Storage API token. For custom tokens, you must additionally provide `KBC_WORKSPACE_SCHEMA`.

4

Can I restrict which tools are available to the AI agent?

Yes. When using HTTP transports, you can set HTTP headers such as `X-Allowed-Tools`, `X-Disallowed-Tools`, or `X-Read-Only-Mode` to control which tools the client can call.

5

How do development branches work?

You can scope all operations to a development branch by setting the `KBC_BRANCH_ID` environment variable or, on remote transports, by including the `X-Branch-Id` header in each request. If not set, the server uses the production branch by default.

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