manage_aws_glue_statements

THE RISK

High Risk

Why manage_aws_glue_statements needs a policy

The name references AWS Glue statements, which in AWS Glue context typically refers to executing statements within interactive Glue sessions (Spark/Python code execution). 'Manage' could also imply create/delete operations. Given the Execute nature of Glue statements (running code in Glue sessions) and the potential for broad data access or modification, Execute is the most appropriate category.

From the tool's definition Tool name 'manage_aws_glue_statements' — no description provided

Documented attack patterns abuse exactly the kind of access manage_aws_glue_statements gives an agent:

POLICY

How to control manage_aws_glue_statements

PolicyLayer is an MCP gateway — it sits between your AI agents and AWS Lambda Tool MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for manage_aws_glue_statements:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "manage_aws_glue_statements": {
      "limits": [
        {
          "counter": "manage_aws_glue_statements_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

manage_aws_glue_statements stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

Create a free account and register AWS Lambda Tool MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

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EXPLORE

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All 805 AWS Lambda Tool MCP Server tools →

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Go deeper

Govern code and CI agents → Branch allowlists, approval on merges, and rate caps on the build and pipeline tools agents trigger.
High-risk tools in AWS Lambda Tool MCP Server → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →
PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about manage_aws_glue_statements

What does the manage_aws_glue_statements tool do? +

manage_aws_glue_statements. It is categorised as a Execute tool in the AWS Lambda Tool MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on manage_aws_glue_statements? +

Register the AWS Lambda Tool MCP Server MCP server in PolicyLayer and add a rule for manage_aws_glue_statements: 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 AWS Lambda Tool MCP Server. Nothing to install.

What risk level is manage_aws_glue_statements? +

manage_aws_glue_statements is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit manage_aws_glue_statements? +

Yes. Add a rate_limit block to the manage_aws_glue_statements 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.

How do I block manage_aws_glue_statements completely? +

Set action: deny in the PolicyLayer policy for manage_aws_glue_statements. 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_statements? +

manage_aws_glue_statements is provided by the AWS Lambda Tool MCP Server MCP server (awslabs.lambda-tool-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every AWS Lambda Tool MCP Server tool call.

Start from AWS Lambda Tool MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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