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gam-seller-mcp-node

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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, everything audited.

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  • Documented (README)
Last scanned: 8/6/2026
Install in Claude Code / Claude Desktop
Method: NPX · gam-seller-mcp-node
Claude Code CLI
claude mcp add gam-seller-mcp-node -- npx -y gam-seller-mcp-node
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "gam-seller-mcp-node": {
      "command": "npx",
      "args": ["-y", "gam-seller-mcp-node"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
Use cases

MCP Servers overview

# GAM Seller MCP Node

[![npm version](https://img.shields.io/npm/v/gam-seller-mcp-node.svg?logo=npm)](https://www.npmjs.com/package/gam-seller-mcp-node)
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[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)
[![TypeScript](https://img.shields.io/badge/TypeScript-5.x-blue.svg)](https://www.typescriptlang.org/)
[![MCP](https://img.shields.io/badge/MCP-2024--11--05-green.svg)](https://modelcontextprotocol.io)

**AI buyer agents are about to participate in programmatic advertising. When they do, they need a governed interface to sell-side inventory — one that cannot be tricked into revealing sensitive data, and that cannot execute transactions it shouldn't.**

This is that interface.

A governed [Model Context Protocol](https://modelcontextprotocol.io) server that exposes sell-side ad inventory (Google Ad Manager and compatible systems) to buyer-side AI agents: discovery, firm pricing, and a soft **commitment** primitive. It performs **no writes to the ad server** — the only mutation it allows is a buyer's own soft commitment (a revocable, TTL-bound intent), never a GAM order or an inventory hold. No raw ad-server access. No sensitive data in responses. Every decision audited.

---

## What problem does this solve?

Sell-side ad inventory (availability, pricing, product structure) lives inside ad servers that hold commercially sensitive and sometimes personal data. Giving an AI buyer agent direct API access to GAM or a similar system creates three risks:

| Risk | Without this project | With this project |
|------|---------------------|-------------------|
| Data over-exposure | Agent can read raw avails, deal IDs, exact floor prices | Only coarse buckets and pre-declared families |
| Accidental writes | Agent SDK can create orders, modify line items | No ad-server writes exist; the only write is a buyer's own soft commitment, which can never become a GAM order or an inventory hold |
| No accountability | API calls are logged but not auditable | Hash-chained audit ledger; every allow/deny recorded |

## How it works

A buyer agent connects via MCP and gets five tools — three read-only, plus a buyer-scoped
commitment primitive (create/revoke) that is the sole write surface:

```
Buyer agent
    │
    ├── well_known_capabilities   ← Signed trust anchor. Check this first.
    │       Returns: RS256-signed capability document, node identity, privacy posture.
    │
    ├── discover_products         ← What can I buy here, and at what firm price?
    │       Returns: product families the buyer is entitled to see (e.g. "Pre-Roll Video"),
    │               each with its firm list price when the publisher has configured one.
    │       Never returns: deal IDs, internal IDs, raw inventory, exact per-impression pricing.
    │
    ├── get_forecast              ← How available is this family next quarter?
    │       Returns: Low / Mid / High availability bucket.
    │       Never returns: exact impression counts, CPM curves, floor prices.
    │
    ├── create_intent             ← Commit to a product at its current firm price (with TTL).
    │       Records a firm, time-boxed buying intent — fail-closed if the price is stale or
    │       mismatched. NOT a GAM order and NOT an inventory hold; it is the handoff artifact
    │       the classic sales rails pick up. Buyer-scoped: you can only ever commit as yourself.
    │
    └── revoke_intent             ← Withdraw one of your own active intents by id.
```

Every call flows through the same pipeline before any domain logic runs:

```
  Buyer request
       │
       ▼
  [SEC-GATE-3]  Replay detection — deduplicate client_request_id
       │
       ▼
  [Auth]        RS256 token validation → identity confirmed or AUTH_FAILED
       │
       ▼
  [Policy]      Surface denylist → entitlement check → scope check (Default-Deny)
       │
       ▼
  [Rate limit]  N=1 / T=30s per buyer_id
       │
       ▼
  [Domain]      Catalog / ForecastEngine — synthetic today, real GAM adapter in progress
       │
       ▼
  [Audit]       Append-only hash-chained ledger, buyer pseudonymized (HMAC)
       │
       ▼
  Response to buyer
```

A bug in any gate fails **closed**, not open.

`create_intent` runs the same gates and adds one more before it records anything: the buyer's
`price_ref` must match the family's current firm price, or the request is rejected — fail-closed on
a stale or mismatched offer, so an intent can never pin a price the publisher is no longer offering.

## Quick start

### Install in an MCP client (via npx)

Add the server to your MCP client (Claude Desktop, Claude Code, Cursor, …):

```jsonc
{
  "mcpServers": {
    "gam-seller": {
      "command": "npx",
      "args": ["-y", "gam-seller-mcp-node"]
    }
  }
}
```

Or run it directly (stdio transport — the default for MCP clients):

```bash
npx -y gam-seller-mcp-node
```

> **Demo mode.** With no config of your own, the node boots on a bundled
> `pilot-publisher` example (illustrative catalog, prices and forecasts) and says so
> on stderr — it starts instead of failing, so you can try the tools immediately.
> Because buyer surfaces always require a token (there is no anonymous path, even in
> demo), the node **prints a ready-to-use demo buyer token** on startup: copy it and pass
> it as the `token` argument to `discover_products` / `get_forecast` to see the example
> families, prices and forecasts.
>
> For a real deployment, point `MCP_CONFIG_DIR` at a directory holding your own
> `deployment.json`, `catalog.json`, `entitlements.json` and `pricing.json`:
>
> ```bash
> MCP_CONFIG_DIR=/etc/gam-seller/config npx -y gam-seller-mcp-node
> ```

### From source

```bash
git clone https://github.com/juan-sibbo/gam-seller-mcp-node.git
cd gam-seller-mcp-node
npm install
npm run build
npm run start:http   # HTTP transport on 127.0.0.1:3900
```

Run the full buyer-agent walkthrough (scripted demo):

```bash
npx tsx demo/run-demo.ts
```

### With Docker

```bash
docker compose up
```

The node starts on `127.0.0.1:3900`. The well-known document is at
`/.well-known/seller-mcp-capabilities`. Persistent volumes for keys and audit data are
pre-configured in `docker-compose.yml`.

### Configure for your publisher

Four JSON files drive all publisher-specific behaviour — no code changes needed. Place them
in `config/` (from-source) or in the directory named by `MCP_CONFIG_DIR` (npx/containerised):

```
deployment.json     # DSR contact, controller model, data retention window
catalog.json        # product families + per-buyer access grants
entitlements.json   # which buyers are entitled to which MCP surfaces
pricing.json        # firm list prices per family (fail-closed on expiry)
```

**Invalid** config always fails closed: a malformed file stops the node rather than running
with a silently different access policy. **Absent** config (no `config/` and no `MCP_CONFIG_DIR`)
drops to the bundled [`config/examples/pilot-publisher/`](config/examples/pilot-publisher/)
example — demo mode, announced on stderr — so the node is never a broken install, only ever a
real deployment or a clearly-labelled demo.

## Why not just use the GAM API directly?

| Approach | Data exposure | Writability | Auditability | AI-agent friendly |
|----------|--------------|-------------|--------------|-------------------|
| Raw GAM API | Everything in the account | Full CRUD | Logging only | Poor (SOAP/REST, no MCP) |
| OpenRTB bid requests | User-level data, floor prices | Bid-only | None | Poor |
| **This server** | Coarse families + bucket forecasts | Buyer's own soft commitment only (no GAM writes) | Hash-chained ledger | Native MCP |

## Current status

Working MVP. The full request pipeline (auth → policy → rate-limit → domain → audit),
the buyer-scoped commitment primitive (`create_intent` / `revoke_intent`, with TTL expiry),
the audit ledger, GDPR data-subject-rights toolkit, Docker packaging, HTTP transport,
and a live interop probe (Python buyer agent simulation) are all implemented and tested.

**Not yet wired**: a live Google Ad Manager connection. The catalog and forecast data are
synthetic, loaded from local config. The GAM ForecastService SOAP adapter interface exists
([`src/forecast/source.ts`](src/forecast/source.ts)) and is the next major milestone.
See the [open issues](https://github.com/juan-sibbo/gam-seller-mcp-node/issues) for the roadmap.

## Architecture

See [`docs/ARCHITECTURE.md`](docs/ARCHITECTURE.md) for the full module map and data-flow diagrams.

Key modules:

| Module | Role |
|--------|------|
| `src/server.ts` | MCP tool definitions + request pipeline |
| `src/policy/` | Default-Deny engine, entitlement store, surface allowlist/denylist |
| `src/identity/` | RS256 key management, token issuance/validation, revocation denylist |
| `src/audit/` | Hash-chained ledger, HMAC pseudonymization, external anchoring |
| `src/pricing/` | Firm list price store, expiry-aware (fail-closed on stale prices) |
| `src/forecast/` | Bucket engine + GAM adapter seam (synthetic today) |
| `src/dsr/` | GDPR Art. 15/17/18/20 data-subject-rights toolkit |
| `src/catalog/` | Product family store, per-buyer access grants |

## Security model

**Default-Deny.** Every request is denied unless an explicit entitlement says otherwise — there
is no "allow by default" path in the code.

**Structural allow/denylist (SEC-GATE-*).** Response surfaces are governed by a fixed list enforced
at the policy layer, independent of which tool was called. Exact pricing, deal IDs, raw availability
numbers, cross-buyer state, real inventory holds (soft-lock), and any ad-server write are permanently
denied. The one permitted write is a buyer's own commitment (`create_inte
adtechai-agentgdprgoogle-ad-managermcpmodel-context-protocolopenrtbprivacy-by-designprogrammatic-advertisingtypescript

What people ask about gam-seller-mcp-node

What is juan-sibbo/gam-seller-mcp-node?

+

juan-sibbo/gam-seller-mcp-node is mcp servers for the Claude AI ecosystem. 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, everything audited. It has 0 GitHub stars and its last recorded update is dated 2026-08-05.

How do I install gam-seller-mcp-node?

+

You can install gam-seller-mcp-node by cloning the repository (https://github.com/juan-sibbo/gam-seller-mcp-node) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is juan-sibbo/gam-seller-mcp-node safe to use?

+

Our security agent has analyzed juan-sibbo/gam-seller-mcp-node and assigned a Trust Score of 95/100 (tier: Verified). See the full breakdown of passed checks and flags on this page.

Who maintains juan-sibbo/gam-seller-mcp-node?

+

juan-sibbo/gam-seller-mcp-node is maintained by juan-sibbo. The last recorded GitHub activity is dated 2026-08-05, with 10 open issues.

Are there alternatives to gam-seller-mcp-node?

+

Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

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