Last updated July 2026
Windsor.ai vs Google Ads MCP: which one should you use?
Windsor.ai pulls data from 325+ sources into dashboards and AI tools. It's a general marketing connector, not an ads tool, with a few basic write actions bolted on. Google's official MCP gives raw GAQL access to your Google Ads account for free, and is read-only. Neither is built to run campaigns through AI. If you need that, that's a different tool.
The short version
| Dimension | ||
|---|---|---|
| What it is | Marketing data pipeline with 325+ connectors and MCP for AI querying | Open-source MCP server for raw GAQL queries against Google Ads |
| Price | Free tier (1 source), $23-598/mo paid plans | Free (open source, self-hosted) |
| Platforms | 325+ sources: Google, Meta, LinkedIn, TikTok, Shopify, HubSpot, and more | Google Ads only |
| Write capability | Basic write actions (via connector) on a few platforms, not built as an ads manager. | None by default. Experimental mutations exist in an unofficial fork. |
| Setup time | ~30 seconds (hosted, OAuth flow) | 15-60+ minutes (Python, Google Cloud project, developer token, OAuth credentials) |
| Who it's for | Marketing teams who need data in dashboards or AI tools | Developers who know GAQL and want free first-party Google Ads data |
Neither is built to run your ads.
Windsor pipes data and has a few basic write actions bolted on. Google's MCP queries data, read-only. Neither creates campaigns, generates creative, or manages ads as a real workflow. If your AI agent needs to research, create, and launch, that requires a purpose-built ads tool.
The details
Breadth vs depth: 325 connectors vs 3 tools
Windsor connects to everything. Google Ads, Meta, LinkedIn, TikTok, Shopify, HubSpot, Salesforce, and 300+ more sources. All piped into one place where you can query across channels. If your question spans multiple platforms, Windsor can answer it.
Google Ads MCP does one thing well. Three tools, raw GAQL, full access to the Google Ads API surface. No abstraction layer. If you know the query language, you get exactly what the API returns. For deep Google Ads analysis, nothing beats first-party access.
The tradeoff is clear. Windsor gives you breadth at the cost of depth (users report it "falls apart" for complex attribution). Google gives you depth at the cost of everything else (one platform, developer-only).
Hosted service vs self-hosted experiment
Windsor is a managed platform. Sign up, OAuth into your ad accounts, data starts flowing. SOC 2 Type II certified, servers in Germany, 7,000+ customers. You pay for reliability.
Google Ads MCP requires Python, a Google Cloud project, a developer token, OAuth credentials, and a credential file. The developer token alone requires a separate application via Google's API Center (review takes days to weeks). After approval, one developer documented spending two extra days troubleshooting Cloud Run deployment after local setup worked. Google explicitly labels it "not intended for production use."
If you're a marketer who wants data accessible now, Windsor wins. If you're a developer who can stomach the application process plus infrastructure setup, Google's MCP costs nothing in dollars.
Neither is an ads manager
Windsor's MCP is built for data retrieval, plus a handful of basic write actions (pause, enable, set a budget) on some platforms. It's a data connector with some ad-write bolted on, not an ads tool, and there's no review step before those actions fire.
Google Ads MCP is read-only by default. An experimental fork (google-marketing-solutions) adds mutation tools behind a flag, but Google warns it's "not officially supported" and executes directly against live accounts with no confirmation gates. No drafts, no undo.
If you want AI to actually manage your ads, full campaign creation, creative, structured workflows, both tools leave you short. You can see what's happening, and do a little about it at best. You can't run a real ads operation on either.
There's a third option
Need a real ads workflow?
Windsor and Google Ads MCP solve the analytics half of the problem. You can query performance data all day. But neither is built for the ads workflow itself.
No campaign creation. Windsor's write actions are minimal (pause, enable, budgets on a few platforms). Google's official MCP can't write at all.
No creative generation. You still need separate tools for ad copy, images, and video hooks.
No draft safety. Windsor's basic actions have no review step. Google's experimental mutations go straight to your live account. No review step, no undo.
AdKit is purpose-built for running ads. Competitor tracking and a 500k+ ad library for research. AI creative studio for generation. Campaign management across Meta, Google, TikTok, Reddit, LinkedIn, X, and Microsoft. And a draft-first MCP where nothing touches your live ad account until you approve it.
Which one fits?
Pick Windsor.ai if you need marketing data in one place.
You pull data from 5+ platforms and need it unified in Looker Studio, BigQuery, or Sheets.
Cross-channel reporting matters more than deep single-platform analysis.
Your team isn't technical. 30-second setup beats 60-minute Python configuration.
You need SOC 2 compliance and a managed service with SLA.
Windsor is ETL infrastructure with a few basic write actions bolted on. Great at piping data. Not built for running ads.
Pick Google Ads MCP if you want free, raw Google Ads data.
Google Ads is your only platform and you know GAQL.
You want first-party data access with zero cost and no vendor lock-in.
You're a developer comfortable with Python, OAuth, and self-hosting.
Experimental status and no SLA don't bother you.
Free and official. Deepest Google Ads data access available. Developer-only.
Pick AdKit if you want the full ads workflow, not just data.
Research what competitors run, generate creative, launch campaigns, and manage performance in one tool.
Meta, Google, TikTok, Reddit, LinkedIn, X, and Microsoft. Campaign management across all seven.
Draft-first safety: nothing touches your live ad account until you approve.
500k+ ad library and competitor tracking for research before you spend.
Marketers, founders running their own ads, agencies. From $29/mo with 7-day free trial.
In-depth comparison
Product category & scope
| Feature | ||
|---|---|---|
| Product type | Marketing data integration platform (ETL + MCP) | Open-source MCP server (raw API access) |
| Primary job | Unify marketing data from 325+ sources for reporting and AI querying | Give LLMs raw GAQL access to Google Ads accounts |
| Target audience | Marketing teams, agencies, data analysts | Developers with Google Ads API experience |
Company & trust
| Built by | Windsor Group AG (acquired by team.blue, Jan 2026) | Google Ads API Team |
| Company location | Switzerland | United States |
| Date founded | 2017 | October 2025 (open-source release) |
| Backing | team.blue (3.3M+ SMB customers, 22 European markets) | Google (Alphabet) |
| Customers | 7,000+ | 512 GitHub stars, community-driven |
| Open Source | Yes | Yes |
| Production ready | Yes | Explicitly experimental, not intended for production |
Data access & capabilities
| Read capability | 325+ sources via scheduled syncs and MCP | Google Ads only, raw GAQL queries |
| Write capability | Basic write actions (via connector) | Disabled by default. Experimental fork only, no safety gates. |
| Campaign creation | No | No |
| Creative generation | No | No |
| Ad library / competitor tracking | No | No |
| Cross-channel reporting | Yes | No |
| Attribution modeling | Yes | No |
| BI tool sync (Looker, Tableau, Power BI) | Yes | No |
| Data warehouse sync (BigQuery, Snowflake) | Yes | No |
MCP & AI integration
| MCP tools | Mostly data retrieval, plus basic actions (pause, enable, budgets) on a few platforms | 3 (search, list_accessible_customers, get_resource_metadata) |
| Transport | Hosted (streamable HTTP + SSE at mcp.windsor.ai) | Self-hosted (stdio local, streamable HTTP for Cloud Run) |
| Query language | Natural language via structured filters | Raw GAQL (Google Ads Query Language) |
| AI client support | Claude, ChatGPT, Gemini, Perplexity, Cursor, n8n | Gemini CLI (primary), Claude Code, Cursor, VS Code |
| Draft system | No draft workflow | No |
Setup & security
| Setup time | ~30 seconds | 15-60+ minutes |
| Technical skill required | None (OAuth flow) | High (Python, Google Cloud, developer token, GAQL) |
| Hosting | Managed (windsor.ai) | Self-hosted (local or Cloud Run) |
| SOC 2 | Type II certified | N/A (open source, self-hosted) |
| SLA | Yes (paid plans) | None |
Pricing
| Free tier | 1 data source, 1 account | Fully free (open source) |
| Entry paid tier | $23/mo (3 sources, 75 accounts) | Free |
| Mid tier | $118/mo (7 sources, hourly syncs) | Free |
| Agency tier | $299-598/mo (10-14 sources, 200-500 accounts) | Free |
| Billing model | Per data source + row volume | N/A |
Frequently asked questions
Need to act on insights, not just read them?
Competitor tracking, creative generation, and a draft-first MCP for Meta, Google, TikTok, Reddit, LinkedIn, X, and Microsoft. From $29/month, 7-day free trial.