get_feedback_scores_analytics
Get raw feedback-score distribution time-series data with per-score buckets. Use this to understand sentiment mix; use get_feedback_weighted_analytics for calibrated scores with weighting.
This record as markdown: /tools/codeswhat-portkey-admin-mcp/get-feedback-scores-analytics.md
What get_feedback_scores_analytics does on Portkey Admin
AI agents call get_feedback_scores_analytics to retrieve information from Portkey Admin without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why get_feedback_scores_analytics is rated Low
This tool retrieves and queries analytics data (feedback score distributions) with no side effects, data modification, or external operations triggered. It is purely informational, allowing users to analyze sentiment metrics. The most severe risk is unauthorized data access if credentials are compromised, but the tool itself performs only read operations.
From the tool's definition Tool description states 'Get raw feedback-score distribution time-series data' - uses 'Get' verb and retrieves analytics data without modification. Returns existing data about feedback scores organized in time-series buckets.
Attacks that exploit this kind of access
The rule that runs get_feedback_scores_analytics safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Portkey Admin, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_feedback_scores_analytics, this is the rule to start with:
get_feedback_scores_analytics is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Portkey Admin, apply this rule, and every get_feedback_scores_analytics call is checked against it from then on.
Questions about get_feedback_scores_analytics
Get raw feedback-score distribution time-series data with per-score buckets. Use this to understand sentiment mix; use get_feedback_weighted_analytics for calibrated scores with weighting. It is categorised as a Read tool in the Portkey Admin MCP Server, which means it retrieves data without modifying state.
Register the Portkey Admin MCP server in PolicyLayer and add a rule for get_feedback_scores_analytics: 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 Portkey Admin. Nothing to install.
get_feedback_scores_analytics 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_feedback_scores_analytics 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_feedback_scores_analytics. 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_feedback_scores_analytics is provided by the Portkey Admin MCP server (codeswhat/portkey-admin-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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