bias_amplification_tracker
Tracks bias amplification in LLM outputs by analyzing fairness metrics from HuggingFace's model leaderboard. Designed for risk assessment personas to detect and quantify demographic, gender, or racial bias amplification in generated text. Accepts model identifiers or output samples, returns struc...
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What bias_amplification_tracker does on Mcp Knowledge
AI agents call bias_amplification_tracker to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
modelId | string | — | HuggingFace model identifier (e.g., 'facebook/opt-1.3b') |
outputSamples | array | — | Array of LLM output strings to analyze for bias amplification |
demographicGroups | array | — | Specific demographic groups to monitor (e.g., ['gender', 'race']) |
Parameters from the server's own tool schema.
Why bias_amplification_tracker is rated Low
This tool reads and analyzes data from HuggingFace's model leaderboard to detect bias metrics. It retrieves and structures fairness information without modifying, executing, or deleting anything. Severity is medium because misuse could involve analyzing sensitive demographic data or being used to circumvent bias detection, though the tool itself is read-only.
From the tool's definition Tracks bias amplification... analyzing fairness metrics... returns structured bias metrics and amplification trends
Attacks that exploit this kind of access
The rule that runs bias_amplification_tracker safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For bias_amplification_tracker, this is the rule to start with:
bias_amplification_tracker 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 Mcp Knowledge, apply this rule, and every bias_amplification_tracker call is checked against it from then on.
Questions about bias_amplification_tracker
Tracks bias amplification in LLM outputs by analyzing fairness metrics from HuggingFace's model leaderboard. Designed for risk assessment personas to detect and quantify demographic, gender, or racial bias amplification in generated text. Accepts model identifiers or output samples, returns structured bias metrics and amplification trends. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.
bias_amplification_tracker accepts 4 parameters: async, modelId, outputSamples, demographicGroups. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for bias_amplification_tracker: 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 Knowledge. Nothing to install.
bias_amplification_tracker 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 bias_amplification_tracker 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 bias_amplification_tracker. 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.
bias_amplification_tracker is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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