programmatic_attribution_calibrator

SERVERGapup Mcp SOURCEhttps://mcp.gapup.io/mcp

Medium RISK CLASS

Category Write

Parameters 63 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

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

WHAT IT DOES

What programmatic_attribution_calibrator does on Gapup Mcp

AI agents use programmatic_attribution_calibrator to create or update resources in Gapup Mcp, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Gapup Mcp environment.

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 Medium

This tool modifies marketing attribution models and their calibration parameters based on impression-level data ingestion. While it does not delete or destroy data (Destructive), nor does it move money directly (Financial), it does create or update model states and attribution records reversibly. The 'calibrates' and 'adjustments' language indicates write/modification operations rather than pure queries.

From the tool's definition Tool 'ingests' and 'calibrates' data, 'accepts model parameters' as input, and 'returns structured calibration metrics and attribution adjustments'. The description indicates data modification of marketing mix models through real-time bidding data processing.

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 Gapup Mcp, 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 Rate-limited

programmatic_attribution_calibrator stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. 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": {
      "limits": [
        {
          "counter": "programmatic_attribution_calibrator_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Gapup Mcp, 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 Write tool in the Gapup Mcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

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 Gapup 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 Gapup Mcp. Nothing to install.

What risk level is programmatic_attribution_calibrator? +

programmatic_attribution_calibrator is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

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 Gapup MCP server (https://mcp.gapup.io/mcp). 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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