programmatic_attribution_calibrator
ActiveTool of @gapup/mcp-knowledge
declared in 0.2.0
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.
Parameters schema
{
"type": "object",
"required": [
"modelId",
"startDate",
"endDate"
],
"properties": {
"async": {
"type": "boolean",
"description": "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 timeouts."
},
"endDate": {
"type": "string",
"format": "date",
"description": "End date for impression data (ISO 8601)"
},
"modelId": {
"type": "string",
"description": "Identifier of the MMM model to calibrate"
},
"startDate": {
"type": "string",
"format": "date",
"description": "Start date for impression data (ISO 8601)"
},
"impressionIds": {
"type": "array",
"items": {
"type": "string"
},
"description": "List of OpenRTB impression IDs to include in calibration"
},
"confidenceThreshold": {
"type": "number",
"default": 0.95,
"maximum": 1,
"minimum": 0,
"description": "Confidence threshold for calibration metrics"
}
}
}No endpoints wrapped at confidence ≥ 0.70.
Parent server
@gapup/mcp-knowledge
https://github.com/getgapup/gapup-mcp
2/7 registries