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 adju...
Part of the Mcp Knowledge server.
Free to start. No card required.
AI agents use programmatic_attribution_calibrator to create or modify resources in Mcp Knowledge. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call programmatic_attribution_calibrator repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Mcp Knowledge.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"programmatic_attribution_calibrator": {
"limits": [
{
"counter": "programmatic_attribution_calibrator_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Mcp Knowledge policy for all 271 tools.
These attack patterns abuse exactly the kind of access programmatic_attribution_calibrator gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
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 Mcp Knowledge MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
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.
programmatic_attribution_calibrator is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
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.
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.
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.
Deterministic rules across all 271 Mcp Knowledge tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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