
Iceberg MCP
IcebergMCP is an MCP server that lets you interact with your Apache Iceberg Lakehouse using natural language in Claude, Cursor, or any other MCP client.
what is Iceberg MCP?
Iceberg MCP is an AI-native Lakehouse Integration server that allows users to interact with their Apache Iceberg Lakehouse using natural language through various MCP clients like Claude and Cursor.
how to use Iceberg MCP?
To use Iceberg MCP, install the required packages, configure your AWS profile, and set up the MCP server in your preferred client. You can then issue natural language queries to interact with your Iceberg tables.
key features of Iceberg MCP?
- Natural language interaction with Iceberg Lakehouse
- Integration with multiple MCP clients
- Tools for retrieving namespaces, tables, schemas, and properties
use cases of Iceberg MCP?
- Querying Iceberg tables using natural language.
- Retrieving metadata about tables and schemas.
- Analyzing data stored in an Iceberg Lakehouse.
FAQ from Iceberg MCP?
- What is required to run Iceberg MCP?
You need an Iceberg catalog managed in AWS Glue and the
uv
package manager installed.
- Can I modify data using Iceberg MCP?
Currently, all tools are read-only and cannot modify or delete data from your lakehouse.
- What clients are supported?
Iceberg MCP can be used with Claude, Cursor, and other MCP clients.
IcebergMCP is a Model Context Protocol (MCP) server that allows interacting with your Apache Iceberg Lakehouse via natural language in Claude, Cursor, or any other MCP client.
Table of Contents
- Installation
- Configuration
- Available Tools
- Examples
- Limitations & Security Considerations
- Contributing
Installation
Prerequisites
- Iceberg catalog managed in AWS Glue
- AWS profile configured on the machine, with access to the catalog
uv
package manager - install viabrew install uv
or 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-1
by default.
Available Tools
The server provides the following tools for interacting with your Iceberg tables:
get_namespaces
: Gets all namespaces in the 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 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_events
table?" - "Generate an SQL query that calculates the sum and the p95 of all number columns in
raw_metrics
for all VIP users fromusers_info
" - "Why did the queries on
raw_events
recently 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
- Iceberg REST Catalog (coming soon!)
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.