Get a sample of rows from a table
AI agents call get_table_sample to retrieve information from MCP PostgreSQL Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves sample data from a table without creating, modifying, deleting, or executing arbitrary operations. It is a straightforward query operation with no side effects, fitting the 'Read' category.
From the tool's definition Tool name 'get_table_sample' and description 'Get a sample of rows from a table' indicate retrieval of data with no modification capability. Server description emphasizes 'read-only access' and 'SELECT statements'.
Attacks that exploit this kind of access
Get a sample of rows from a table. It is categorised as a Read tool in the MCP PostgreSQL Server MCP Server, which means it retrieves data without modifying state.
Register the MCP PostgreSQL Server MCP server in PolicyLayer and add a rule for get_table_sample: 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 MCP PostgreSQL Server. Nothing to install.
get_table_sample is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_table_sample 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 get_table_sample. 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.
get_table_sample is provided by the MCP PostgreSQL Server MCP server (kristofer84/mcp-postgres). 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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