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juan-sibbo/gam-seller-mcp-node

by Various

Governed, read-only MCP server for sell-side ad inventory discovery. AI buyer agents get coarse availability forecasts and product families — nothing sensitive, nothing writable, e

MCP

juan-sibbo/gam-seller-mcp-node

Added 8 Sept 2026

#adtech #ai-agent #gdpr #google-ad-manager #mcp #model-context-protocol #openrtb #privacy-by-design

Overview

A read-only MCP server that exposes sell-side ad inventory data to AI buyer agents. It provides coarse availability forecasts and product family information, with all access governed and audited.

Best for

Best for
AI buyer agents that need safe, audited access to sell-side ad inventory data.

Use cases

  • Let AI buyer agents query available ad inventory before bidding
  • Retrieve coarse availability forecasts for planning campaigns
  • Discover product families for targeting or contextual analysis

Notes

A read-only MCP server that exposes sell-side ad inventory data to AI buyer agents. It provides coarse availability forecasts and product family information, with all access governed and audited.

0 stars on GitHub. Last updated 2026-09-07. Licensed MIT.

Use cases

  • Let AI buyer agents query available ad inventory before bidding
  • Retrieve coarse availability forecasts for planning campaigns
  • Discover product families for targeting or contextual analysis

Pros

  • Read-only design prevents accidental modifications
  • Governed access and audit trail support compliance
  • Simple TypeScript implementation for easy integration

Cons

  • Forecasts are coarse, not granular or real-time
  • Limited to sell-side discovery, no buying or optimization features
  • Early-stage project with no community traction yet

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Read-only design prevents accidental modifications
  • Governed access and audit trail support compliance
  • Simple TypeScript implementation for easy integration

Cons

  • Forecasts are coarse, not granular or real-time
  • Limited to sell-side discovery, no buying or optimization features
  • Early-stage project with no community traction yet
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