retail_media_attribution_bridge
Provides unified attribution insights for retail media and programmatic campaigns by analyzing MMM signals from FreeWheel Marketplace and Common Crawl. Designed for ad revenue operations teams to bridge cross-channel performance gaps. Accepts campaign IDs, date ranges, and channel filters as inpu...
This record as markdown: /tools/io-github-getgapup-gapup-mcp/retail-media-attribution-bridge.md
What retail_media_attribution_bridge does on Gapup Mcp
AI agents call retail_media_attribution_bridge to retrieve information from Gapup Mcp 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 attribution window (YYYY-MM-DD) |
channels | array | — | Channels to include in analysis |
startDate | string | Yes | Start date for attribution window (YYYY-MM-DD) |
campaignIds | array | Yes | List of campaign identifiers to analyze |
confidenceThreshold | number | — | Minimum confidence score for included signals |
Parameters from the server's own tool schema.
Why retail_media_attribution_bridge is rated Low
The tool retrieves and analyzes attribution data from existing sources (FreeWheel Marketplace and Common Crawl), returning structured read-only insights. It accepts campaign IDs, date ranges, and channel filters as input parameters but does not create, modify, delete, or trigger any financial transactions. The blast radius is low as misuse would at most expose campaign performance data.
From the tool's definition Provides unified attribution insights... analyzing MMM signals... Returns structured attribution data with source provenance and confidence scores
Attacks that exploit this kind of access
The rule that runs retail_media_attribution_bridge 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 retail_media_attribution_bridge, this is the rule to start with:
retail_media_attribution_bridge 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 Gapup Mcp, apply this rule, and every retail_media_attribution_bridge call is checked against it from then on.
Questions about retail_media_attribution_bridge
Provides unified attribution insights for retail media and programmatic campaigns by analyzing MMM signals from FreeWheel Marketplace and Common Crawl. Designed for ad revenue operations teams to bridge cross-channel performance gaps. Accepts campaign IDs, date ranges, and channel filters as input. Returns structured attribution data with source provenance and confidence scores. It is categorised as a Read tool in the Gapup Mcp MCP Server, which means it retrieves data without modifying state.
retail_media_attribution_bridge accepts 6 parameters: async, endDate, channels, startDate, campaignIds, confidenceThreshold. Required: endDate, startDate, campaignIds. The full parameter table on this page comes from the server's own tool schema.
Register the Gapup MCP server in PolicyLayer and add a rule for retail_media_attribution_bridge: 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.
retail_media_attribution_bridge 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 retail_media_attribution_bridge 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 retail_media_attribution_bridge. 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.
retail_media_attribution_bridge 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.
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