# programmatic_attribution_calibrator

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.

Agent View of the PolicyLayer registry record for `programmatic_attribution_calibrator`. HTML page: https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/programmatic-attribution-calibrator

## Facts

- Tool: `programmatic_attribution_calibrator`
- Server: Mcp Knowledge (`https://mcp.gapup.io`) — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge.md
- Homepage: https://github.com/getgapup/gapup-mcp
- Risk category: Read (Low risk)
- Registry record: grade F, identity unverified
- Server auth posture: open
- Server rate-limited: no
- Parameters: 6 (3 required)
- Recommended policy verdict: Allowed

## Parameters

| Parameter | Type | Required | Description |
| --- | --- | --- | --- |
| `async` | boolean | no | 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 | no | List of OpenRTB impression IDs to include in calibration |
| `confidenceThreshold` | number | no | Confidence threshold for calibration metrics |

Parameters from the server's own tool schema.

## Example call (MCP tools/call, JSON-RPC 2.0)

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "programmatic_attribution_calibrator",
    "arguments": {
      "endDate": "<endDate>",
      "modelId": "<modelId>",
      "startDate": "<startDate>"
    }
  }
}
```

## 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 own definition: "calibrates marketing mix models...ingesting OpenRTB impression-level data...returning structured calibration metrics and attribution adjustments"

## Use case

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.

## Recommended policy (PolicyLayer)

Verdict: **Allowed**. Enforced by the PolicyLayer MCP gateway (https://policylayer.com/mcp-gateway) before a call reaches Mcp Knowledge:

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

## Other tools on Mcp Knowledge (270)

- `adversarial_input_stress_tester` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/adversarial-input-stress-tester.md
- `competitor_pricing_scrape` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/competitor-pricing-scrape.md
- `dora_operational_resilience_stress_tes` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/dora-operational-resilience-stress-tes.md
- `financial_model_3statement` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/financial-model-3statement.md
- `gl_reconciler` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/gl-reconciler.md
- `lgpd_data_subject_rights_automator` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/lgpd-data-subject-rights-automator.md
- `monte_carlo_portfolio` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/monte-carlo-portfolio.md
- `workflow_orchestrator` — Execute — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/workflow-orchestrator.md
- `ma_arbitrage_hunter` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ma-arbitrage-hunter.md
- `repo_rate_arbitrage_scanner` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/repo-rate-arbitrage-scanner.md
- `tax_optimization` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/tax-optimization.md
- `treasury_optimizer` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/treasury-optimizer.md
- `usdc_x402_payments_intel` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/usdc-x402-payments-intel.md
- `working_capital_fx_hedge_optimizer` — Financial — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/working-capital-fx-hedge-optimizer.md
- `pricing_in_deal` — Other — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/pricing-in-deal.md
- `term_sheet_negotiation` — Other — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/term-sheet-negotiation.md
- `abm_architect` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/abm-architect.md
- `abm_lookalike_account_finder` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/abm-lookalike-account-finder.md
- `account_expansion_mapper` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/account-expansion-mapper.md
- `affiliate_fraud_clickstream_detector` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/affiliate-fraud-clickstream-detector.md
- `africa_trade_barrier_breaker` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-barrier-breaker.md
- `africa_trade_finance_esg_rater` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-finance-esg-rater.md
- `africa_trade_preference_arbitrage` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-preference-arbitrage.md
- `africa_trade_preference_optimizer` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/africa-trade-preference-optimizer.md
- `agoa_eba_intelligence` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/agoa-eba-intelligence.md
- `ai_act_sandbox_regulatory_sandbox` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-act-sandbox-regulatory-sandbox.md
- `ai_act_training_data_audit` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-act-training-data-audit.md
- `ai_governance_full_report_async` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-governance-full-report-async.md
- `ai_governance_full_report_result` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-governance-full-report-result.md
- `ai_governance_pilot` — Read — https://policylayer.com/tools/io-github-getgapup-mcp-knowledge/ai-governance-pilot.md
- …and 240 more: https://policylayer.com/tools/io-github-getgapup-mcp-knowledge.md

## For agents

This record is a snapshot. Live verdicts and the full registry:

- Check every server in your MCP config at once: `npx -y policylayer stack`
- Vet a server before you add it: install the mcp-precheck skill — `npx skills add https://policylayer.com` (skill text: https://policylayer.com/skill.md)
- Query the registry over MCP: endpoint `https://api.policylayer.com/mcp` — tools `check_mcp_server`, `check_mcp_stack`, `check_tool`, `search_registry`, `get_change_events`

---

Source: the PolicyLayer MCP registry — one continuously verified record per MCP server. Full record: https://policylayer.com/registry?q=io-github-getgapup-mcp-knowledge · API: https://policylayer.com/registry/api · Policy library: https://policylayer.com/policies/io-github-getgapup-mcp-knowledge