Dry-run-first Google Ads search-term intent analyzer and negative-keyword MCP for agents.
β If this agent-first tool helps your workflow, please star the repo. Stars make this tooling easier for other builders to discover and help Delx keep shipping open infrastructure.
π§± Part of the Delx agent stack β 15 open-source MCP servers across body, reach and coordination.
Dry-run-first Google Ads search-term intent analyzer for agents. It helps Codex, Claude, Cursor, Hermes, OpenClaw and other MCP clients classify search terms, protect buyer intent and draft negative-keyword plans from CSV exports before any live account change.
Use it when an agent needs to reduce wasted spend without accidentally excluding buyer-intent queries.
Not shipped. Optional FastMCP extra is stdio-only (same skip as delx-agent-utilities: no /health without extra Starlette routes). Dry-run analysis stays request-stateless over stdio.
Google Ads cleanup is risky when agents act directly on accounts. This package makes the safe path the default:
manifest, connection_status and privacy_audit before action toolspipx install google-ads-intent-mcp
With MCP support:
pipx install "google-ads-intent-mcp[mcp]"
Published on PyPI: google-ads-intent-mcp. Release automation uses PyPI Trusted Publishing, so GitHub Actions can publish future versions without long-lived PyPI tokens. See docs/pypi-publishing.md.
google-ads-intent manifest --client codex
google-ads-intent doctor
google-ads-intent privacy-audit
google-ads-intent classify "free robux generator no verification"
google-ads-intent analyze-csv --csv examples/search_terms.csv
google-ads-intent plan-negatives --csv examples/search_terms.csv
The classifier is a deterministic, dependency-free heuristic with broad,
cross-vertical signal coverage (ecommerce, B2B/SaaS, local services, health,
finance, education and more) β not just gaming traffic. It sorts each search
term into waste, buyer, research or competitor intent and protects
converting queries from being flagged as negatives.
An optional LLM/embeddings-backed refinement path is available and is off by default. It requires no extra dependencies or API keys for normal use, and always falls back to the heuristic when no backend is configured:
# Opt in via flag (falls back to the heuristic if nothing is configured)
google-ads-intent --llm classify "crm software pricing"
# Or via environment variable
GOOGLE_ADS_INTENT_LLM=1 google-ads-intent analyze-csv --csv export.csv
To actually call a backend, set OPENAI_API_KEY (and optionally
GOOGLE_ADS_INTENT_LLM_MODEL, default gpt-4o-mini) and install the openai
package. Without those, --llm is a no-op that keeps the heuristic result.
Each classification reports which path produced it via a source
(heuristic or llm) field.
google-ads-intent-mcp
Hermes-style config:
mcp_servers:
google_ads_intent:
command: google-ads-intent-mcp
args: []
sampling:
enabled: false
Recommended first calls:
google_ads_connection_statusgoogle_ads_privacy_auditgoogle_ads_analyze_search_termsgoogle_ads_build_negative_plan| Tool | Purpose |
|---|---|
google_ads_agent_manifest | Install/runtime guidance for agent clients |
google_ads_connection_status | CSV/API readiness without credentials |
google_ads_privacy_audit | Dry-run, account and export boundaries |
google_ads_classify_search_term | Single-query intent classification |
google_ads_analyze_search_terms | Batch CSV-style analysis |
google_ads_build_negative_plan | Dry-run negative keyword plan |
Use google-ads-intent-mcp. First call google_ads_connection_status and google_ads_privacy_audit.
Analyze the search terms, protect buyer/conversion queries, and return a dry-run negative plan only.
The parser accepts common exported columns such as:
search_term, Search term, Querycost, Cost, cost_microsclicks, Clicksconversions, Conversions, Conv.impressions, Impr., Impressionspython3 -m venv .venv
. .venv/bin/activate
pip install -e ".[dev]"
pytest
python -m compileall -q src
Source-derived launch command. Check the maintainerβs required arguments and credentials before running:
uvx google-ads-intent-mcpMerge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.
{
"mcpServers": {
"io-github-davidmosiah-google-ads-intent-mcp": {
"command": "uvx",
"args": [
"google-ads-intent-mcp"
]
}
}
}Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the clientβs tool list, then try a read-only example from its documentation.
Claude Desktop setup referencegoogle-ads-intent-mcppypiio.github.davidmosiah/google-ads-intent-mcp works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.
~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.~/.cursor/mcp.jsonRestart Cursor for changes to take effect..vscode/mcp.jsonReload VS Code window for changes to take effect.~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect..mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.