Execute a SQL file in dry-run mode - actually runs ALL statements within a transaction, captures REAL results for each (row counts, errors with line numbers, constraint violations), then ROLLBACK so nothing persists. Perfect for testing migrations before deploying. Returns detailed error info inc...
AI agents invoke dry_run_sql_file to trigger actions in Postgres. 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.
This tool executes arbitrary SQL code with real transactional consequences during the dry-run phase. Although designed defensively with rollback, the execution itself constitutes running database operations whose effects depend on the SQL arguments provided.
From the tool's definition Executes SQL statements within a transaction and captures REAL results including row counts, errors, and constraint violations.
Attacks that exploit this kind of access
Execute a SQL file in dry-run mode - actually runs ALL statements within a transaction, captures REAL results for each (row counts, errors with line numbers, constraint violations), then ROLLBACK so nothing persists. Perfect for testing migrations before deploying. Returns detailed error info including PostgreSQL error codes, constraint names, and hints to help quickly fix issues. Warns about non-rollbackable operations (sequences, VACUUM, etc.). Optionally use server/database/schema params for one-time execution on a different server. It is categorised as a Execute tool in the Postgres MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Postgres MCP server in PolicyLayer and add a rule for dry_run_sql_file: 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 Postgres. Nothing to install.
dry_run_sql_file 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 dry_run_sql_file 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 dry_run_sql_file. 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.
dry_run_sql_file is provided by the Postgres MCP server (teja-sudo/postgres-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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