manage_aws_glue_databases
AI agents use manage_aws_glue_databases to create or update resources in Amazon SageMaker AI MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Amazon SageMaker AI MCP Server environment.
Without a description, we infer from the name that this tool performs management operations on AWS Glue databases. 'Manage' suggests write operations that can create or modify database configurations and metadata. This is classified as Write rather than Destructive because 'manage' does not explicitly indicate deletion.
From the tool's definition Tool name 'manage_aws_glue_databases' indicates modification of AWS Glue database resources. The verb 'manage' typically implies create, update, or modify operations on databases.
Attacks that exploit this kind of access
manage_aws_glue_databases. It is categorised as a Write tool in the Amazon SageMaker AI MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for manage_aws_glue_databases: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Amazon SageMaker AI MCP Server. Nothing to install.
manage_aws_glue_databases is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the manage_aws_glue_databases rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for manage_aws_glue_databases. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
manage_aws_glue_databases is provided by the Amazon SageMaker AI MCP Server MCP server (awslabs.sagemaker-ai-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.