> ## ⚠️ IMPORTANT: YOU ARE RESPONSIBLE FOR YOUR AGENTS > > You are solely responsible for the actions and permissions of agents using the MCP server. > > - By default, the MCP server operates in **read-only mode**. > - To enable write access, you must **explicitly configure the MCP with the necessary IAM permissions** and use "--allow-write" flag to enable create and append operations on S3 Tables using the MCP server. > - Always follow the **principle of least privilege**—grant only the permissions necessary for the agent to function. > - If enabling write operations, **we recommend you take a backup of your data** and carefully validate any instructions generated by your LLM before execution. > - With AWS S3 Tables MCP Server, we recommend exercising caution when integrating it into automated workflows. > > Misconfigured permissions or unverified agent actions may result in **data loss, failed operations, or unexpected LLM behavior**. An AWS Labs Model Context Protocol (MCP) server for AWS S3 Tables that enables AI assistants to interact with S3-based table storage.
This server provides the following tools for AI assistants:
Create and list S3 Table Buckets to organize your tabular data at scale. (No delete or update operations supported.)
Define and list namespaces within table buckets for logical data separation and organization. (No delete or update operations supported.)
Create, rename, and list individual tables within namespaces for flexible data modeling. (No delete or general update operations; only renaming is supported.)
Retrieve maintenance settings for tables and buckets. (Read-only; no update or delete.)
Access resource policies for tables and buckets to control access and security. (Read-only; no update or delete.)
View detailed table metadata, including schema and storage information. Metadata file can be updated.
Run **read-only** SQL queries directly against S3 Tables for seamless data analysis and reporting. For write operations, only **appending new data** (inserts) is supported; updates and deletes via SQL are not available.
Automatically create S3 Tables from CSV files uploaded to S3, streamlining data ingestion and onboarding. (No delete or update of tables via this operation.)
Discover and access comprehensive bucket metadata through the S3 Metadata Table for enhanced data governance and cataloging. (Read-only.)
`~/Library/Logs`
`~/AppData/Local/Logs`