google-ads-meta-ads-mcp
Consolidates fragmented marketing data streams into a single interface, enabling automated performance analysis and cross-platform reporting without the over…
Google Ads MCP server + Meta Ads MCP (Facebook Ads MCP) + Google Analytics MCP (GA4) + Search Console in one hosted remote MCP for Claude, ChatGPT, Cursor & n8n: OAuth login, no API keys, approval-gated writes, 7-day free trial. By Ryze AI.
- Analyze performance data across Google Ads and Meta Ads in one conversation
- Generate reports combining Google Analytics data with search console insights
- Ask Claude to compare ad spend and conversion metrics from multiple platforms
Consolidates fragmented marketing data streams into a single interface, enabling automated performance analysis and cross-platform reporting without the overhead of managing multiple API keys or complex authentication flows.
Data-driven marketing teams and consultants requiring unified access to Google and Meta advertising metrics via LLM-based workflows.
https://github.com/irinabuht12-oss/google-ads-meta-ads-mcp
By irinabuht12-oss
How to Get It
claude mcp add google-ads-meta-ads-mcp -- npx -y google-ads-meta-ads-mcp
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Help me analyze performance data across Google Ads and Meta Ads in one conversation
Trust Signals Auto-scanned
Data & Access
Community Pulse Quiet
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 6,129 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 6,129 GitHub stars; contributors unknown; last commit 0d ago; license MIT.