Gadschain — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Gadschain (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<!-- mcp-name: io.github.SnipMCP/gadschain -->
The AI layer between your Google Ads account and your marketing decisions.
Battle-tested. Six tools cover the daily-ops loop — campaign listing, search-term review, budget tuning, pause/enable, and negative-keyword grooming. All responses are strict Pydantic models. No raw protobuf reaches the agent.
GadsChain Demo
The open-source server runs locally with your own API keys. For hosted infrastructure with multi-account failover, SLA guarantees, and webhook alerts — join the managed cloud waitlist.
Raw Google Ads API returns thousands of rows. One bad campaign structure bleeds budget silently. GadsChain reads, sanitizes, and acts on your ad data before waste compounds.
git clone https://github.com/SnipMCP/gadschain.git
cd gadschain
pip install -e ".[dev]"
cp .env.example .envOr with Docker:
docker-compose up --buildGOOGLE_ADS_DEVELOPER_TOKEN=your_developer_token_here
GOOGLE_ADS_CLIENT_ID=your_oauth_client_id_here
GOOGLE_ADS_CLIENT_SECRET=your_oauth_client_secret_here
GOOGLE_ADS_REFRESH_TOKEN=your_refresh_token_here
GOOGLE_ADS_LOGIN_CUSTOMER_ID=1234567890 # MCC (manager), digits only
GOOGLE_ADS_CUSTOMER_ID=1234567890 # default operating account
GOOGLE_ADS_API_VERSION=v24
LOG_LEVEL=INFOThree example prompts to send to Claude (or any MCP-compatible agent):
Use get_campaigns to show me which campaigns are bleeding budget this monthRun get_search_terms for the last 30 days and tell me which queries are wasting spendAdd "free", "cheap", "jobs" as negative keywords to campaign 12345# Tab 1 — start the MCP server
python -m gadschain.server# Tab 2 — call a tool from a Python shell or your MCP client
# Tool signatures:
# get_campaigns(customer_id=None)
# get_search_terms(customer_id=None, days=30, campaign_id=None)
# update_budget(campaign_id, new_budget_dollars, customer_id=None)
# pause_campaign(campaign_id, customer_id=None)
# enable_campaign(campaign_id, customer_id=None)
# add_negative_keywords(campaign_id, keywords, match_type="BROAD", customer_id=None)Three layers between raw Google Ads output and your model:
Google Ads API → [Fetch] → [Transform] → [Act] → MCP Tool → AI Agent
GAQL micros→$ safe
queries enum→str mutations
CTR→% shared-budget guardSELECT *, no protobuf pagination footguns.REMOVED blocked on status changes, shared budgets refused (shared_budget_refused), match types validated before any mutate call. The agent never gets an exception; it gets a structured {"error": ..., "message": ...} it can reason about.RAW GOOGLE ADS PAYLOAD GADSCHAIN OUTPUT
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Impressions: 3,389 Spend (28d): $51.41
Clicks: 163 Conversions: 3 ($17.14 each)
CTR: 4.81% Conv. rate: 1.84%
Cost/click: $0.32 avg Surface: Display Network waste
identified on Fridays
($0.11 CPC vs $0.44 avg)In one read of a real account, GadsChain surfaced $51.41 spent over 28 days for 3 conversions at $17.14 each — a 1.84% conversion rate hidden inside a 4.81% CTR that looks healthy on paper. The Display Network was the silent culprit, with Friday clicks averaging $0.11 CPC vs the $0.44 search-side average — cheap junk traffic inflating CTR while contributing nothing to conversions. The agent saw it because the transformed payload made channel attribution legible instead of buried in protobuf.
PRs welcome. Run pytest before submitting.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.