
Apache Iceberg
Access Apache Iceberg tables stored in AWS through natural language queries in Claude or other MCP clients. Explore catalogs, schemas, and partition information without writing code.
Provides direct access to Apache Iceberg tables stored in AWS, enabling exploration of catalogs, schemas, properties, and partition information without complex queries or code.
What it does
- Browse Apache Iceberg catalogs and schemas
- Inspect table properties and metadata
- View partition information
- Query table structures using natural language
- Access AWS Glue managed catalogs
Best for
About Apache Iceberg
Apache Iceberg is a community-built MCP server published by ryft-io that provides AI assistants with tools and capabilities via the Model Context Protocol. Access Apache Iceberg tables in AWS: explore catalogs, schemas, properties and partitions—no queries or code required. It is categorized under databases, analytics data.
How to install
You can install Apache Iceberg in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
License
Apache Iceberg is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
IcebergMCP is a Model Context Protocol (MCP) server that lets you interact with your Apache Iceberg™ Lakehouse using natural language in Claude, Cursor, or any other MCP client.
Table of Contents
- Installation
- Configuration
- Available Tools
- Examples
- Limitations & Security Considerations
- Contributing
Installation
Prerequisites
- Apache Iceberg™ catalog managed in AWS Glue
- AWS profile configured on the machine, with access to the catalog
uvpackage manager - install viabrew install uvor see official installation guide
Claude
-
Inside Claude, go to Settings > Developer > Edit Config > claude_desktop_config.json
-
Add the following:
{
"mcpServers": {
"iceberg-mcp": {
"command": "uv", // If uv can't be found, replace with full absolute path to uv
"args": [
"run",
"--with",
"iceberg-mcp",
"iceberg-mcp"
],
"env": {
"ICEBERG_MCP_PROFILE": "<aws-profile-name>"
}
}
}
}
Cursor
-
Inside Cursor, go to Settings -> Cursor Settings -> MCP -> Add new global MCP server
-
Add the following:
{
"mcpServers": {
"iceberg-mcp": {
"command": "uv", // If uv can't be found, replace with full absolute path to uv
"args": [
"run",
"--with",
"iceberg-mcp",
"iceberg-mcp"
],
"env": {
"ICEBERG_MCP_PROFILE": "<aws-profile-name>"
}
}
}
}
Configuration
Environment variables can be used to configure the AWS connection:
ICEBERG_MCP_PROFILE- The AWS profile name to use. This role will be assumed and used to connect to the catalog and the object storage. If not specified, the default role will be used.ICEBERG_MCP_REGION- The AWS region to use. This is used to determine the catalog and object storage location.us-east-1by default.
Available Tools
The server provides the following tools for interacting with your Apache Iceberg™ tables:
get_namespaces: Gets all namespaces in the Apache Iceberg™ catalogget_iceberg_tables: Gets all tables for a given namespaceget_table_schema: Returns the schema for a given tableget_table_properties: Returns table properties for a given table, like total size and record countget_table_partitions: Gets all partitions for a given table
Examples
Once installed and configured, you can start interacting with your Apache Iceberg™ tables through your MCP client. Here are some simple examples of how to interact with your lakehouse:
- "List all namespaces in my catalog"
- "List all tables for the namespace called
bronze" - "What are all the string columns in the table
raw_events? - "What is the size of the
raw_eventstable?" - "Generate an SQL query that calculates the sum and the p95 of all number columns in
raw_metricsfor all VIP users fromusers_info" - "Why did the queries on
raw_eventsrecently become much slower?"
Limitations & Security Considerations
- All tools are currently read-only and cannot modify or delete data from your lakehouse
- Currently supported catalogs:
- AWS Glue
- Apache Iceberg™ REST Catalog (coming soon!)
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
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