mcp/s3-tables-mcp-server pulls statistics

AWS S3 Tables MCP Server

Manage S3 Tables for analytics.

What is an MCP Server?

MCP Info

Attribute	Details
Docker Image	mcp/s3-tables-mcp-server
Author	awslabs
Repository	https://github.com/awslabs/mcp

Image Building Info

Attribute	Details
Dockerfile	https://github.com/awslabs/mcp/blob/636aca8e109b5559006044f035bb89c16e9e5410/src/s3-tables-mcp-server/Dockerfile
Commit	636aca8e109b5559006044f035bb89c16e9e5410
Docker Image built by	Docker Inc.
Docker Scout Health Score
Verify Signature	COSIGN_REPOSITORY=mcp/signatures cosign verify mcp/s3-tables-mcp-server --key https://raw.githubusercontent.com/docker/keyring/refs/heads/main/public/mcp/latest.pub
Licence	Apache License 2.0

Available Tools (16)

Tools provided by this Server	Short Description
append_rows_to_table	Append rows to an Iceberg table using PyIceberg/Daft.
create_namespace	Create a new namespace in an S3 table bucket.
create_table	Create a new S3 table in an S3 table bucket.
create_table_bucket	Creates an S3 table bucket.
get_bucket_metadata_config	Get the metadata table configuration for a regular general purpose S3 bucket.
get_maintenance_job_status	Get the status of a maintenance job for a table.
get_table_maintenance_config	Get details about the maintenance configuration of a table.
get_table_metadata_location	Get the location of the S3 table metadata.
import_csv_to_table	Import data from a CSV file into an S3 table.
import_parquet_to_table	Import data from a Parquet file into an existing S3 table.
list_namespaces	List all namespaces across all S3 table buckets.
list_table_buckets	List all S3 table buckets for your AWS account.
list_tables	List all S3 tables across all table buckets and namespaces.
query_database	Execute SQL queries against S3 Tables using PyIceberg/Daft.
rename_table	Rename an S3 table or move it to a different S3 namespace.
update_table_metadata_location	Update the metadata location for an S3 table.

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Tools Details

Tool: append_rows_to_table

Append rows to an Iceberg table using PyIceberg/Daft.

This tool appends data rows to an existing Iceberg table using the PyIceberg engine. The rows parameter must be a list of dictionaries, each representing a row. Check the schema of the table before appending rows.

Example input values: warehouse: 'arn:aws:s3tables:<Region>:<accountID>:bucket/<bucketname>' region: 'us-west-2' namespace: 'retail_data' table_name: 'customers' rows: [{"customer_id": 1, "customer_name": "Alice"}, ...] uri: 'https://s3tables.us-west-2.amazonaws.com/iceberg' catalog_name: 's3tablescatalog' rest_signing_name: 's3tables' rest_sigv4_enabled: 'true'

Parameters	Type	Description
namespace	string	The name of the namespace. Must be 1-255 characters long and contain only alphanumeric characters, underscores, and hyphens.
region	string	AWS region for S3Tables/Iceberg REST endpoint
rows	array	List of rows to append, each as a dict
table_name	string	The name of the table. Must be 1-255 characters long and contain only alphanumeric characters, underscores, and hyphens.
uri	string	REST URI for Iceberg catalog
warehouse	string	Warehouse string for Iceberg catalog
catalog_name	string optional	Catalog name
rest_signing_name	string optional	REST signing name
rest_sigv4_enabled	string optional	Enable SigV4 signing

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Tool: create_namespace

Create a new namespace in an S3 table bucket.

Creates a namespace. A namespace is a logical grouping of tables within your S3 table bucket, which you can use to organize S3 tables.

Permissions: You must have the s3tables:CreateNamespace permission to use this operation.

Parameters	Type	Description
namespace	string	The name of the namespace. Must be 1-255 characters long and contain only alphanumeric characters, underscores, and hyphens.
table_bucket_arn	string	Table bucket ARN
region_name	string optional	The AWS region name where the operation should be performed.

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Tool: create_table

Create a new S3 table in an S3 table bucket.

Creates a new S3 table associated with the given S3 namespace in an S3 table bucket. The S3 table can be configured with specific format and metadata settings. Metadata contains the schema of the table. Do not use the metadata parameter if the schema is unclear.

Supported Iceberg Primitive Types:

• boolean: True or false
• int: 32-bit signed integers (can promote to long)
• long: 64-bit signed integers
• float: 32-bit IEEE 754 floating point (can promote to double)
• double: 64-bit IEEE 754 floating point
• decimal(P,S): Fixed-point decimal with precision P and scale S (precision must be 38 or less)
• date: Calendar date without timezone or time
• time: Time of day, microsecond precision, without date or timezone
• timestamp: Timestamp, microsecond precision, without timezone (represents date and time regardless of zone)
• timestamptz: Timestamp, microsecond precision, with timezone (stored as UTC)
• string: Arbitrary-length character sequences (UTF-8 encoded)

Note: Binary field types (binary, fixed, uuid) are not supported.…