This record as markdown: /tools/io-github-devopam-mcpg/run-maintenance.md
What run_maintenance does on Mcpg
AI agents invoke run_maintenance 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.
Why run_maintenance is rated High
The tool performs server-side operations that execute code/commands (maintenance procedures) rather than merely reading data. While not explicitly destructive in the sense of deleting data, maintenance commands modify database structure and can have significant effects.
From the tool's definition Tool named 'run_maintenance' on a production PostgreSQL MCP server with sibling tools that manage policies, analyze queries, and optimize indexing suggests this tool triggers database maintenance operations (e.g., VACUUM, ANALYZE, or reindex).
Attacks that exploit this kind of access
The rule that runs run_maintenance 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_maintenance, this is the rule to start with:
run_maintenance 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcpg, apply this rule, and every run_maintenance call is checked against it from then on.
Questions about run_maintenance
run_maintenance 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.
Register the Mcpg MCP server in PolicyLayer and add a rule for run_maintenance: 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.
run_maintenance is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the run_maintenance 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 run_maintenance. 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.
run_maintenance 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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