programmatic_attribution_calibrator

SERVERMcp Knowledge SOURCEhttps://mcp.gapup.io

Low RISK CLASS

Category Read

Parameters 63 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-getgapup-mcp-knowledge/programmatic-attribution-calibrator.md

WHAT IT DOES

What programmatic_attribution_calibrator does on Mcp Knowledge

AI agents call programmatic_attribution_calibrator 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
`endDate`	string	Yes	End date for impression data (ISO 8601)
`modelId`	string	Yes	Identifier of the MMM model to calibrate
`startDate`	string	Yes	Start date for impression data (ISO 8601)
`impressionIds`	array	—	List of OpenRTB impression IDs to include in calibration
`confidenceThreshold`	number	—	Confidence threshold for calibration metrics

Parameters from the server's own tool schema.

RISK

Why programmatic_attribution_calibrator is rated Low

The tool ingests data and returns calibration metrics/adjustments — it reads and analyzes impression-level ad data to produce analytical outputs. While 'calibration' and 'attribution adjustments' sound like modifications, the description frames them as computed outputs/recommendations rather than writing changes back to a system.

From the tool's definition calibrates marketing mix models...ingesting OpenRTB impression-level data...returning structured calibration metrics and attribution adjustments

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs programmatic_attribution_calibrator 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 programmatic_attribution_calibrator, this is the rule to start with:

programmatic_attribution_calibrator Allowed

programmatic_attribution_calibrator is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "programmatic_attribution_calibrator": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every programmatic_attribution_calibrator call is checked against it from then on.

FAQ

Questions about programmatic_attribution_calibrator

What does the programmatic_attribution_calibrator tool do? +

For ad_revenue_ops persona: calibrates marketing mix models (MMM) by ingesting OpenRTB impression-level data from FreeWheel Marketplace and other programmatic sources. Accepts model parameters, date ranges, and impression IDs as input, returning structured calibration metrics and attribution adjustments. Useful for improving model accuracy with real-time bidding data and validating revenue attribution across programmatic channels. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.

What parameters does programmatic_attribution_calibrator accept? +

programmatic_attribution_calibrator accepts 6 parameters: async, endDate, modelId, startDate, impressionIds, confidenceThreshold. Required: endDate, modelId, startDate. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on programmatic_attribution_calibrator? +

Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for programmatic_attribution_calibrator: 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.

What risk level is programmatic_attribution_calibrator? +

programmatic_attribution_calibrator is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit programmatic_attribution_calibrator? +

Yes. Add a rate_limit block to the programmatic_attribution_calibrator 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.

How do I block programmatic_attribution_calibrator completely? +

Set action: deny in the PolicyLayer policy for programmatic_attribution_calibrator. 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.

What MCP server provides programmatic_attribution_calibrator? +

programmatic_attribution_calibrator 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.

KEEP EXPLORING

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