MCP Iceberg Catalog

Name: MCP Iceberg Catalog
Author: ahodroj

@ahodroj

关于 MCP Iceberg Catalog

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

基本信息

分类

AI 与智能体

运行时

python

传输方式

stdio

发布者

ahodroj

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

工具

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概览

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.