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.
README
GAM Seller MCP Node
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:
- Default-Deny. Every request is denied unless an explicit entitlement says otherwise. There is no "allow by default" path.
- 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.
- 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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