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MCP Iceberg Catalog

@ahodroj

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MCP Iceberg Catalog について

MCP server for interacting with Apache Iceberg catalog from Claude, enabling data lake discovery and metadata search through a LLM prompt.

#mcp-iceberg#data-lake#metadata-search

基本情報

カテゴリ

AI とエージェント

ランタイム

python

トランスポート

stdio

公開者

ahodroj

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": {
    "mcp-iceberg-service": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli",
        "install",
        "@ahodroj/mcp-iceberg-service",
        "--client",
        "claude"
      ]
    }
  }
}

ツール

ツールは検出されませんでした

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 MCP Iceberg Catalog?

MCP Iceberg Catalog is a Model Context Protocol server implementation that provides a SQL interface for querying and managing Apache Iceberg tables through Claude Desktop. It integrates with Iceberg REST catalogs and S3-compatible storage for data lake operations.

How to use MCP Iceberg Catalog?

Install via Smithery using npx -y @smithery/cli install @ahodroj/mcp-iceberg-service --client claude or configure Claude Desktop manually by adding a claude_desktop_config.json entry with the uv command and environment variables ICEBERG_CATALOG_URI, ICEBERG_WAREHOUSE, and optionally S3_ENDPOINT, AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY. Requires Python 3.10+, UV or pip, and access to an Iceberg REST catalog and S3 storage.

Key features of MCP Iceberg Catalog

  • SQL interface for Iceberg tables via Claude Desktop
  • Supports LIST TABLES, DESCRIBE TABLE, SELECT, and INSERT operations
  • Built on pyiceberg for catalog and table operations
  • Uses PyArrow for efficient data handling
  • Integrates with REST catalogs and S3-compatible storage

Use cases of MCP Iceberg Catalog

  • Querying and exploring Iceberg tables through natural language in Claude Desktop
  • Inserting data into Iceberg tables using SQL commands
  • Managing table metadata and schemas interactively
  • Building data lake applications with AI-assisted interfaces

FAQ from MCP Iceberg Catalog

What dependencies does MCP Iceberg Catalog require?

Python 3.10 or higher, UV package installer (recommended) or pip, access to an Iceberg REST catalog, and S3-compatible storage.

What operations are currently supported?

The server supports LIST TABLES, DESCRIBE TABLE, SELECT, and INSERT operations. UPDATE, DELETE, CREATE TABLE, and ALTER TABLE are listed as future implementations.

How is data accessed and stored?

Data is stored in an Iceberg REST catalog and S3-compatible storage. The server connects via REST catalog URIs and uses PyIceberg for table operations and PyArrow for data handling.

What transport does the server use?

The server communicates with Claude Desktop through stdio using the Model Context Protocol.

Are there any known limitations?

Complex data types (arrays, maps, structs), timestamp with timezone, decimals, nested fields, batch inserts, authentication, role-based access, and transaction support are not yet implemented and are listed as future work.

コメント

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