manage_aws_glue_sessions

// WHEN AI AGENTS USE THIS TOOL

AI agents use manage_aws_glue_sessions to create or modify resources in Amazon Data Processing MCP Server. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

// WHY ENFORCE A POLICY ON MANAGE_AWS_GLUE_SESSIONS

Without a policy, an AI agent could call manage_aws_glue_sessions repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Amazon Data Processing MCP Server.

// RECOMMENDED POLICY

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

amazon-data-processing-mcp-server.yaml

tools:
  manage_aws_glue_sessions:
    rules:
      - action: allow
        rate_limit:
          max: 30
          window: 60

See the full Amazon Data Processing MCP Server policy for all 36 tools.

// DETAILS

Tool Name manage_aws_glue_sessions

Category Write

MCP Server Amazon Data Processing MCP Server MCP Server

Risk Level Medium

// MORE AMAZON DATA PROCESSING MCP SERVER TOOLS

Write add_inline_policy Write create_data_processing_role Write manage_aws_athena_data_catalogs Write manage_aws_athena_databases_and_tables Write manage_aws_athena_named_queries Write manage_aws_athena_query_executions Write manage_aws_athena_workgroups Write manage_aws_emr_clusters

View all 36 tools →

// WHAT CAN GO WRONG

Agents calling write-class tools like manage_aws_glue_sessions have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

// OTHER WRITE TOOLS ACROSS MCP SERVERS

Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.

Firecrawl Web Scraping Server firecrawl_generate_llmstxt AbraFlexi contact_create AbraFlexi contact_update AbraFlexi evidence_create AbraFlexi evidence_update AbraFlexi invoice_issued_update

// RELATED READING

// FAQ

What does the manage_aws_glue_sessions tool do? +

Manage AWS Glue Interactive Sessions for running Spark and Ray workloads. This tool provides operations for creating and managing Glue Interactive Sessions, which enable interactive development and execution of Spark ETL scripts and Ray applications. Interactive sessions provide a responsive environment for data exploration, debugging, and iterative development. ## Requirements - The server must be run with the `--allow-write` flag for create-session, delete-session, and stop-session operations - Appropriate AWS permissions for Glue Interactive Session operations ## Operations - **create-session**: Create a new interactive session with specified configuration - **delete-session**: Delete an existing interactive session - **get-session**: Retrieve detailed information about a specific session - **list-sessions**: List all interactive sessions with optional filtering - **stop-session**: Stop a running interactive session ## Example ```python # Create a new Spark ETL session { 'operation': 'create-session', 'session_id': 'my-spark-session', 'role': 'arn:aws:iam::123456789012:role/GlueInteractiveSessionRole', 'command': {'Name': 'glueetl', 'PythonVersion': '3'}, 'glue_version': '3.0', } ``` Args: ctx: MCP context operation: Operation to perform session_id: ID of the session description: Description of the session role: IAM Role ARN command: Session command configuration timeout: Number of minutes before session times out idle_timeout: Number of minutes when idle before session times out default_arguments: Map of key-value pairs for session arguments connections: Connections to use for the session max_capacity: Number of Glue DPUs to allocate number_of_workers: Number of workers to use worker_type: Type of predefined worker security_configuration: Name of the SecurityConfiguration structure glue_version: Glue version to use tags: Map of key-value pairs (tags) for the session request_origin: Origin of the request max_results: Maximum number of results to return next_token: Pagination token Returns: CallToolResult with operation status and data. It is categorised as a Write tool in the Amazon Data Processing MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on manage_aws_glue_sessions? +

Add a rule in your Intercept YAML policy under the tools section for manage_aws_glue_sessions. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Amazon Data Processing MCP Server MCP server.

What risk level is manage_aws_glue_sessions? +

manage_aws_glue_sessions is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit manage_aws_glue_sessions? +

Yes. Add a rate_limit block to the manage_aws_glue_sessions rule in your Intercept 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.

How do I block manage_aws_glue_sessions completely? +

Set action: deny in the Intercept policy for manage_aws_glue_sessions. 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.

What MCP server provides manage_aws_glue_sessions? +

manage_aws_glue_sessions is provided by the Amazon Data Processing MCP Server MCP server (awslabs.aws-dataprocessing-mcp-server). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

manage_aws_glue_sessions

Let agents act without letting them run wild.