Dry-run-first Google Ads search-term intent analyzer and negative-keyword MCP for agents.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
mcp-name: io.github.davidmosiah/google-ads-intent-mcp
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 toolsWith MCP support:
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.
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:
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.
Hermes-style config:
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 |
The parser accepts common exported columns such as:
search_term, Search term, Querycost, Cost, cost_microsclicks, Clicksconversions, Conversions, Conv.impressions, Impr., ImpressionsNo reviews yet β be the first to share how this listing worked for you.
Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.
[](https://allmcps.com/mcp/google-ads-intent-mcp)<a href="https://allmcps.com/mcp/google-ads-intent-mcp"><img src="https://allmcps.com/api/badge/google-ads-intent-mcp?style=directory" alt="Google Ads Intent MCP on AllMCPs" /></a>