This record as markdown: /tools/io-github-devopam-mcpg/repack-table.md
What repack_table does on Mcpg
AI agents invoke repack_table 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 repack_table is rated High
Table repacking is a maintenance operation (like pg_repack in PostgreSQL) that rebuilds a table to reclaim bloat without a full lock. It is an Execute-level operation as it triggers significant database restructuring. However, the empty description lowers confidence — it could also be destructive if it overwrites table data irreversibly.
From the tool's definition Tool name 'repack_table'; description is empty and uninformative.
Attacks that exploit this kind of access
The rule that runs repack_table 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 repack_table, this is the rule to start with:
repack_table 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 repack_table call is checked against it from then on.
Questions about repack_table
repack_table 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 repack_table: 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.
repack_table 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 repack_table 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 repack_table. 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.
repack_table 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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