google-ads-cowork-OS

Open-source Google Ads MCP server plus a paid-search skill pack.

This repo now ships two layers:

• MCP server tools for live Google Ads reads and mutations
• Structured workflow skills in /skills so an agent behaves like a performance marketer instead of a confused SQL intern with a developer token

Google already ships an official Google Ads MCP server:

• Docs: https://developers.google.com/google-ads/api/docs/developer-toolkit/mcp-server
• Repo: https://github.com/googleads/google-ads-mcp

That server is useful, but intentionally narrow:

• read-only
• GAQL-focused
• Python-based

Austin's Cowork thread showed the more interesting pattern:

• Google Ads data access via MCP
• marketer workflows encoded as skills
• approval-gated mutations
• useful output formats with reasoning and auditability
• works on desktop and Dispatch, not just a laptop dev setup

This repo is built around that idea.

From https://x.com/helloitsaustin/status/2036553581625745511 and the surrounding thread:

• his plugin uses the official GAQL MCP as the read layer
• mutations are wired separately through the Google Ads API
• the value comes from skills, not just raw access
• confirmed skill/workflow pattern includes:
  • mine-search-terms
  • search-term-methodology
  • budget optimizations
  • weekly reviews
  • reporting
• search term outputs include a reasoning column for auditability
• mutations require explicit approval

That is the right model, so this repo copies the architecture and expands the skill suite.

This is not supposed to be a "set bids with AI" toy.

The useful version of Google Ads automation is:

• observe
• recommend
• approve
• apply

In practice, that means:

• recommendation-first
• mutation-second
• strong guardrails
• structured outputs
• concrete GAQL examples
• auditability for every meaningful change

This repo was shaped from five inputs:

• Austin's full X thread and follow-ups
• Google's official GAQL MCP server and docs
• broader public Google Ads MCP / skill ecosystems
• local marketing skill inventory
• best-practice research on Google Ads automation and PPC operations

Common pattern across the ecosystem:

• MCP servers handle live data and mutations
• skills/plugins encode workflow logic
• the best systems behave like operator copilots, not autonomous budget arsonists

• list_accessible_customers
• search_gaql
• get_campaign_performance
• get_ad_group_performance
• get_keyword_performance
• get_search_terms
• list_campaigns
• list_ad_groups
• list_ads

• create_campaign
• update_campaign
• create_ad_group
• update_ad_group
• create_keyword
• update_keyword
• create_responsive_search_ad
• update_responsive_search_ad
• update_campaign_budget
• set_entity_statuses

Inside /skills:

• search-term-methodology.md
• mine-search-terms.md
• budget-optimization.md
• weekly-review.md
• reporting.md
• negative-keyword-management.md
• campaign-health-check.md
• bid-management.md
• ad-copy-analysis.md
• competitor-analysis.md
• product-marketing-context.md
• google-ads-audit-framework.md
• cep-write-operations.md
• strategy-stack.md

These skills are structured markdown workflows with:

• description
• when to use
• required inputs
• step-by-step method
• evaluation criteria
• output format
• safety/approval notes
• CEP write protocol where relevant
• example GAQL queries

Public repo and skill-library scans pushed this repo in four important directions:

• Read-first core inspired by public Google Ads MCP baselines
• Audit / reporting / mutation separation instead of one giant blob skill
• CEP write safety: Confirm → Execute → Post-check
• Negative keyword hygiene as a first-class workflow, including future room for conflict cleanup and shared list propagation

Useful public references included:

• google-marketing-solutions/google_ads_mcp
• cohnen/mcp-google-ads
• gomarble-ai/google-ads-mcp-server
• AgriciDaniel/claude-ads
• itallstartedwithaidea/google-ads-skills

The best idea stolen from the public internet, respectfully, is this: raw tools are table stakes. The real value is safe workflow packaging.

The core Austin-style loop is here and expanded:

• mine terms by spend and intent
• evaluate them with a repeatable methodology
• recommend negatives with collision checks
• produce CSV-ready outputs with reasoning
• support approval-gated mutation prep

• month-aware pacing
• overspend and underspend detection
• budget-limited winner detection
• reallocation recommendations instead of dumb blanket cuts

• weekly performance review structure
• operator summary vs stakeholder summary
• root-cause tagging
• action queues and approval separation

• campaign health triage
• tracking, budget, query quality, rank, and creative checks
• Smart Bidding oversight with anti-thrashing rules
• manual CPC and target sanity review where relevant

• RSA/ad copy analysis
• asset gap detection
• pinning warnings
• competitor and auction-insights interpretation
• fight / flank / avoid decision framing

• reusable product-marketing context for ads and landing pages
• strategy stack doc that maps companion skills outside this repo

This repo focuses on the Google Ads operator layer, but it gets much stronger when paired with adjacent marketing skills like:

• paid-ads
• ad-creative
• analytics-tracking
• ab-test-setup
• competitive-ads-extractor
• landing-page-architecture
• page-cro
• form-cro
• copywriting
• marketing-psychology
• hormozi-hooks
• hormozi-value-equation
• competitor-alternatives

Those are referenced in skills/strategy-stack.md so the repo can grow into a fuller paid-acquisition system without turning into a junk drawer.

google-ads-mcp/
├── .env.example
├── .eslintignore
├── .gitignore
├── LICENSE
├── README.md
├── eslint.config.js
├── package.json
├── tsconfig.json
├── examples/
│   ├── claude-desktop-config.json
│   ├── prompt-examples.md
│   └── workflows.md
├── skills/
│   ├── README.md
│   ├── search-term-methodology.md
│   ├── mine-search-terms.md
│   ├── budget-optimization.md
│   ├── weekly-review.md
│   ├── reporting.md
│   ├── negative-keyword-management.md
│   ├── campaign-health-check.md
│   ├── bid-management.md
│   ├── ad-copy-analysis.md
│   ├── competitor-analysis.md
│   ├── product-marketing-context.md
│   └── strategy-stack.md
└── src/
    ├── config.ts
    ├── gaql.ts
    ├── googleAdsClient.ts
    ├── index.ts
    ├── logger.ts
    ├── tools.ts
    └── types.ts

You need:

• Node.js 20+
• a Google Ads API developer token
• a Google Cloud OAuth client
• a refresh token for a user with Google Ads access
• a Google Ads customer ID
• optionally a manager account login customer ID

npm install
npm run build

Copy .env.example to .env and fill in:

GOOGLE_ADS_CLIENT_ID=
GOOGLE_ADS_CLIENT_SECRET=
GOOGLE_ADS_REFRESH_TOKEN=
GOOGLE_ADS_DEVELOPER_TOKEN=
GOOGLE_ADS_CUSTOMER_ID=
GOOGLE_ADS_LOGIN_CUSTOMER_ID=
GOOGLE_ADS_PROJECT_ID=
GOOGLE_ADS_MCP_LOG_LEVEL=info

npm run dev

or:

npm run build
npm start

See examples/claude-desktop-config.json.

Minimal example:

{
  "mcpServers": {
    "google-ads": {
      "command": "node",
      "args": ["/absolute/path/to/google-ads-mcp/dist/index.js"],
      "env": {
        "GOOGLE_ADS_CLIENT_ID": "...",
        "GOOGLE_ADS_CLIENT_SECRET": "...",
        "GOOGLE_ADS_REFRESH_TOKEN": "...",
        "GOOGLE_ADS_DEVELOPER_TOKEN": "...",
        "GOOGLE_ADS_CUSTOMER_ID": "1234567890",
        "GOOGLE_ADS_LOGIN_CUSTOMER_ID": "0987654321"
      }
    }
  }
}

• "List my accessible Google Ads customers."
• "Show campaign performance for the last 30 days."
• "Which keywords spent the most in the last 14 days?"
• "Pull search terms for campaign 123456 over the last 7 days."
• "List active RSAs and their headlines."

• "Run mine-search-terms for the last 30 days and give me a CSV-style output with reasoning for every flagged query."
• "Use search-term-methodology to classify these 100 search terms into keep, watchlist, negative, or keyword candidate."
• "Run a weekly-review and tell me what changed, why it changed, and what needs approval."
• "Prepare budget-optimization recommendations for this month, but do not apply anything."
• "Run a competitor-analysis and tell me whether we should fight, flank, or avoid on these campaigns."

• "Create a paused Search campaign called Brand Search US with a $50/day budget."
• "Create an ad group called Core Terms in campaign 1234567890."
• "Add phrase match keyword 'anthropic api pricing' to ad group 9876543210."
• "Pause these three keywords."
• "Raise the campaign budget to 80000000 micros."
• "Queue these negative keywords for approval but don't apply them yet."

This repo uses the Node library google-ads-api and authenticates with:

• client ID
• client secret
• refresh token
• developer token
• customer ID
• optional login customer ID

That is the simplest practical route for an open-source Node MCP server people can self-host.

Google Ads mutations are real writes, so the repo is designed around an approval-aware model.

Recommended policy:

• Auto-safe: reports, audits, summaries, draft queues
• Review required: keyword adds, negative adds outside safe taxonomies, budget reallocations, ad launches, bid target changes
• Manual only: structural rebuilds, tracking changes, broad-match expansion at scale, brand-risky edits

Hard guardrail ideas encoded into the skills:

• never mutate when tracking is unhealthy
• never push high-impact changes without a preview/diff
• never auto-apply risky negatives
• avoid repeated Smart Bidding thrash
• never recommend Broad Match with Manual CPC as a casual default
• prefer pause over remove for most operational changes
• new entities should usually launch paused first
• require reasoning and confidence labels
• keep an audit trail for recommended and applied actions

Because the repo is meant to be:

• easy to publish
• easy to extend
• easy to slot into Node-heavy agent stacks

This is a strong open-source base, not the last form of every Google Ads workflow.

Current strengths:

• Search-style account operations
• search term mining
• keyword and RSA workflows
• approval-aware mutation prep
• budgets and status changes
• workflow skill packaging

Good next extensions:

• Performance Max deeper support
• labels
• shared negative list helpers
• recommendation ingestion and filtering
• anomaly detection as first-class tools
• change-history driven rollback helpers
• landing-page/CRO integrations

npm run typecheck
npm run build
npm run lint

This repo is public-ready as an open-source base:

• clean TypeScript MCP server
• structured skills directory
• examples and env template
• MIT license
• docs that explain the read + write + skill architecture

Before trusting it with real money, do two boring but necessary things:

1. validate one full read workflow with live credentials
2. validate one mutation workflow in a test account

That last part is less sexy than the demo, but it's how you avoid becoming the world's smartest intern who accidentally set fire to a budget.