Analyze index effectiveness and identify unused or redundant indexes.
AI agents call analyze_index_effectiveness to retrieve information from Postgres without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool performs analysis and reporting on existing database indexes. It retrieves and examines metadata about index usage and effectiveness but does not create, modify, or delete any data or database objects. This is a Read operation—specifically a diagnostic query with no destructive or reversible side effects.
From the tool's definition Tool name contains 'analyze' and description states it identifies/analyzes indexes without modifying them: 'Analyze index effectiveness and identify unused or redundant indexes.' This is a diagnostic query operation with no side effects.
Documented attack patterns abuse exactly the kind of access analyze_index_effectiveness gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Postgres, and nothing reaches the server without passing your rules. This is the rule we recommend for analyze_index_effectiveness:
{
"version": "1",
"default": "deny",
"tools": {
"analyze_index_effectiveness": {}
}
}analyze_index_effectiveness is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Analyze index effectiveness and identify unused or redundant indexes. It is categorised as a Read tool in the Postgres MCP Server, which means it retrieves data without modifying state.
Register the Postgres MCP server in PolicyLayer and add a rule for analyze_index_effectiveness: 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.
analyze_index_effectiveness 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 analyze_index_effectiveness 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 analyze_index_effectiveness. 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.
analyze_index_effectiveness is provided by the Postgres MCP server (mukul975/postgres-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Postgres, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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239 Postgres tools catalogued and risk-classified — across an index of 43,000+ MCP servers.