GAM Seller MCP Node

GAM Seller MCP Node

A governed, read-only MCP server for ad inventory discovery from Google Ad Manager, exposing three tools (well_known_capabilities, discover_products, get_forecast) to buyer-side agents without modifying or accessing the ad server.

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GAM Seller MCP Node

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A governed, read-only Model Context Protocol server that exposes ad-inventory discovery from the sell side (Google Ad Manager and similar systems) to buyer-side agents — without ever touching the ad server itself, and without a buyer agent ever being able to create, modify, or transact anything.

Buyer agents get three tools:

  • well_known_capabilities — a signed, publicly cacheable document describing what this node can do and its privacy posture. This is the trust anchor a buyer checks before anything else.
  • discover_products — coarse product families (e.g. "Pre-Roll Video") a given buyer is entitled to see. No raw inventory, no pricing, no IDs internal to the ad server.
  • get_forecast — a bucketized (Low / Mid / High) availability forecast for a family and period. No exact numbers, ever.

Why it's built this way

Ad servers hold commercially sensitive and sometimes personal data. A seller who wants to expose inventory discovery to AI buyer-agents without opening a door into their ad server needs three guarantees, enforced in code rather than by policy document:

  1. Default-Deny. Every request is denied unless an explicit entitlement says otherwise. There is no "allow by default" path.
  2. Nothing sensitive crosses the boundary. A fixed allowlist of response surfaces exists; everything else (exact pricing, deal IDs, raw availability, order/media-buy operations) is on a permanent denylist that cannot be reached from any tool, now or by future extension.
  3. Every decision is auditable and tamper-evident. Every allow/deny is written to an append-only, hash-chained ledger with external anchoring, so a compromised or malicious operator can't quietly rewrite history.

See docs/DESIGN-PRINCIPLES.md for the reasoning behind each of these, and docs/ARCHITECTURE.md for how the modules fit together.

Status

Early, working MVP. The core request pipeline (auth → policy → rate-limit → domain logic → audit), the audit ledger, and a GDPR data-subject-rights toolkit are implemented and tested. There is currently no live connection to Google Ad Manager — the catalog and forecast data are synthetic, loaded from local config. Wiring a real GAM-backed adapter behind the same policy boundary is the next major milestone, not yet built.

Running it

npm install
npm run build
npm start            # stdio transport (default, for MCP-host clients)
npm run start:http   # HTTP transport on 127.0.0.1:3900
npm test             # full suite (vitest)
npx tsx demo/run-demo.ts   # scripted walkthrough of all three tools + the audit trail

Configuring for a deployment

Catalog and legal/DSR settings are driven by JSON files under config/, no code changes needed:

config/deployment.json     # DSR contact, controller model, retention window
config/catalog.json        # product families + which buyers can see which families
config/entitlements.json   # which buyers are entitled to which surfaces/scopes

All three fail closed: an invalid or missing file stops the node from starting rather than running with a silently different access set than intended.

Switching to a different publisher is just swapping these three files — no code change. config/examples/pilot-publisher/ is a worked example: copy its three JSONs over config/*.json (or bind-mount them in docker-compose.yml) and restart the node.

Data protection

This node treats buyer identity as pseudonymous by design: raw buyer_id values never enter the audit ledger, only an HMAC pseudonym. A dsr/toolkit.ts implements export, restriction, and erasure of a buyer's data (GDPR Art. 15/17/18/20) against exactly what this node stores — nothing more, since it stores nothing about end users, only B2B buyer organizations.

License

MIT — see LICENSE.

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