run_ddl

A execute tool on the Mcpg MCP server.

SERVERMcpg SOURCEpypi:mcpg

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-devopam-mcpg/run-ddl.md

WHAT IT DOES

What run_ddl does on Mcpg

AI agents invoke run_ddl to trigger actions in Mcpg. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.

RISK

Why run_ddl is rated High

DDL operations execute SQL commands that alter database structure. While the tool could be Destructive if it permits DROP/ALTER/TRUNCATE statements, the name alone suggests general DDL execution capability. Without a description confirming it prevents destructive operations, this is classified as Execute (code/command execution) rather than Read or Write.

From the tool's definition Tool name 'run_ddl' indicates execution of Data Definition Language statements (CREATE, ALTER, DROP, etc.) against a PostgreSQL database.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs run_ddl safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Mcpg, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For run_ddl, this is the rule to start with:

run_ddl Rate-limited

run_ddl 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.

View as policy code

policy.json

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

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mcpg, apply this rule, and every run_ddl call is checked against it from then on.

FAQ

Questions about run_ddl

What does the run_ddl tool do? +

run_ddl is a execute tool on the Mcpg MCP server. It is categorised as a Execute tool in the Mcpg MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on run_ddl? +

Register the Mcpg MCP server in PolicyLayer and add a rule for run_ddl: 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 Mcpg. Nothing to install.

What risk level is run_ddl? +

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

Can I rate-limit run_ddl? +

Yes. Add a rate_limit block to the run_ddl 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 run_ddl completely? +

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

run_ddl is provided by the Mcpg MCP server (pypi:mcpg). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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