Quantum ADS MCP
A sovereign Google marketing-agency control plane over the Model Context Protocol, enabling an AI agent to safely operate 20 Google marketing products with read and guarded write capabilities.
README
<div align="center">
<img src="assets/banner.svg" alt="quantum-ads-mcp — sovereign Google marketing-agency control plane" width="880">
quantum-ads-mcp
The most complete open Model Context Protocol control plane for the Google marketing stack — 20 connectors, read + guarded write, Ed25519 signed audit, OAuth 2.1 multi-tenant.
Architecture · The 20 connectors · Install · Configure · Safety · Roadmap
</div>
A sovereign Google marketing-agency control plane over the Model Context Protocol: a shared core (multi-tenant auth, version resilience, a GAQL/query engine, a safety spine with a signed audit ledger) and 20 pluggable per-product connectors spanning the entire Google marketing stack. Built for an AI agent to operate that stack at full granularity, safely.
Status. The full connector surface is built and tested at the logic layer: read + guarded write across 20 products, every tool exercised by mocked tests (no live SDK needed). The per-product live SDK glue is isolated in
sdk.pymodules and smoke-gated (verified against real APIs with your own credentials, not in CI). Remaining for full production hardening: remote OAuth 2.1 transport + multi-tenant secret store + observability (see Roadmap). Read-only by default. Every "most X" claim here is meant to be verifiable.
Contents
Why · The 20 connectors · Architecture · Core · Install · Configure · Run · Safety & honest claims · Roadmap
Architecture
flowchart TD
Client["MCP client (AI agent)"] -->|"stdio · or OAuth 2.1 HTTP (multi-tenant)"| Server["FastMCP server"]
Server --> Core["Sovereign core: auth · version resilience · GAQL/query engine · safety spine (read-only default + Ed25519 signed audit) · registry / meta-tool"]
Core --> C1["google_ads · ga4 · gtm · merchant"]
Core --> C2["datamanager · searchconsole · youtube"]
Core --> C3["dv360 · cm360 · sa360"]
Core --> C4["bigquery · adh · looker · meridian"]
Core --> C5["vertex · trends · gbp · language · workspace · recaptcha"]
C1 -. "smoke-gated sdk.py" .-> G["Google APIs (Ads v24, GA4, GTM, Merchant, …)"]
C4 -. "smoke-gated sdk.py" .-> G
Why this exists
Surveying June 2026: Google's official MCP is read-only (3 tools); the best open write-capable servers are pinned to sunsetting API versions, untested, single-product, or have no safety layer; the capable commercial ones are closed and remote-only. No open, self-hostable server is simultaneously complete across the stack, write-capable, safe, tested, version-resilient, and multi-product. Quantum ADS fills that gap.
The 20 connectors
| Domain | Connectors |
|---|---|
| Paid media | Google Ads (v24), DV360, CM360, SA360 |
| Measurement | GA4 (Data + Admin), Data Manager API (Customer Match + conversions), Search Console |
| Catalog / tagging | Merchant API, Google Tag Manager (+ server-side, Consent Mode v2) |
| Channels | YouTube (Data + Analytics + Reporting), Business Profile, Trends |
| Warehouse / BI / MMM | BigQuery (cost-guarded), Ads Data Hub, Looker, Meridian (Bayesian MMM) |
| Creative / ops | Vertex AI (Gemini / Imagen 4 / Veo 3), Cloud Translation + NL, Workspace (Sheets/Drive/Slides), reCAPTCHA Enterprise |
Full tool catalog, backend keys, and required SDK packages: CONNECTORS.md.
Core (shared by every connector)
- Multi-tenant auth + secret store — credentials load from env / secret manager and never reach the LLM.
- Version resilience — pinned v24, sunset guard (days-until-sunset), unknown-enum tolerance (survives Google's monthly API releases and the 2026-06-10 DV360 Demand Gen rollout).
- Query engine — GAQL build / validate (single-FROM, no-
OR, segment rules, 37-month cap) / stream / flatten, with quota token-buckets + exponential backoff. SA360 uses the same query shape. - Safety spine — read-only by default; every mutation is guarded:
validate_onlypreview → two-step confirm token → Ed25519 signed audit ledger. Consent-aware (Data Manager / Consent Mode v2) and cost-aware (BigQuery dry-run, $6.25/TiB). - Connector registry + meta-tool discovery (
list_capabilities,describe_tool) and env-based connector selection (QUANTUM_ADS_CONNECTORS) so the tool list stays focused.
Install
git clone https://github.com/Casius999/quantum-ads-mcp.git
cd quantum-ads-mcp
uv sync --extra dev
uv run pytest -m "not live" # 250+ tests, no credentials needed
Per-connector live SDKs (e.g. google-analytics-data, google-api-python-client,
google-cloud-bigquery) are installed only when you wire a connector's live backend — see
CONNECTORS.md. The core + mocked test suite need none of them.
Configure
Credentials load from environment variables (no secrets on disk):
GOOGLE_ADS_USE_PROTO_PLUS=True
GOOGLE_ADS_API_VERSION=v24
GOOGLE_ADS_DEVELOPER_TOKEN=...
GOOGLE_ADS_CLIENT_ID=....apps.googleusercontent.com
GOOGLE_ADS_CLIENT_SECRET=...
GOOGLE_ADS_REFRESH_TOKEN=...
QUANTUM_ADS_READ_ONLY=true # writes refused until set to false
QUANTUM_ADS_CONNECTORS=google_ads,ga4,gtm # optional: mount a subset (default: all 19)
Never commit
.env,google-ads.yaml, orclient_secret*.json— all gitignored, andgitleaksruns in CI. See SECURITY.md.
Run
python -m quantum_ads # stdio MCP server
Wire it into your MCP client (Claude Desktop / VS Code) as a stdio server.
Safety & honest claims
Read-only by default; tokens never reach the model; zero secrets in the repo. CI runs lint, strict type-check, the full test suite (≥90% coverage gate), CodeQL, OpenSSF Scorecard, and gitleaks.
The defensible "most powerful" claim is coverage breadth + engineering rigor + safety + version resilience, each verifiable — not "record ad performance" (that depends on budget, creative, and Google's auction, not the server). Documentation states only what the test suite proves; the per-product live SDK calls are smoke-gated and labelled as such.
Roadmap (remaining for full production hardening)
Remote Streamable HTTP + OAuth 2.1/PKCE transport · multi-tenant secret store (per-client OAuth) · observability (structured logging + tracing) · live-API conformance suite · optional anchoring of the signed audit ledger.
License
MIT — see LICENSE.
— Julien Compain · NovaQuantiX
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。