Marketing data is broken for AI.
We reviewed every marketing MCP server on GitHub. They all hit the same three walls — raw data dumps, bloated tool definitions, and configuration that doesn't scale. Agentcy was built to solve all three.
Raw Data Dumps
Your AI gets data, not answers
MCP servers return massive JSON blobs — thousands of lines of raw API responses dumped straight into your conversation. Your AI has to parse it, figure out what matters, and try to give you something useful.
A single GA4 query returns ~5,000 tokens of raw JSON. A WooCommerce order pull? 23,000+. Cross-source queries can exceed 25,000 tokens of raw data — before your AI even starts thinking about your question.
tokens of raw data per query
Context Window Overload
Your workspace shrinks before you start
Every MCP server you install injects its tool definitions into every single message. Install a handful of marketing MCPs and you've consumed most of your context window before asking a single question.
Covering just GA4, Google Ads, Search Console, WooCommerce, YouTube, and SEO requires ~198 tool definitions — consuming roughly 140,000 tokens. That's 70% of a 200K context window eaten by tool definitions alone, before you ask a single question.
tokens consumed by tool definitions
Configuration Nightmare
Managing MCP servers doesn't scale
Some MCP servers hardcode your account in the config — switch clients and you're editing JSON and restarting. Others make you pass property IDs in every single query. Either way, each service is independent — GA4 needs a property ID, Ads needs a customer ID, GSC needs a site URL. For one client, that's 5+ IDs to track. For twenty, it's unmanageable.
There's no concept of a "client" that links your GA4 property to your Ads account to your Search Console site. No portal, no credential isolation, no way to switch everything at once. Agencies on GitHub are filing issues about this exact problem — and the MCP protocol itself has no multi-tenant mechanism.
IDs to manage across 20 clients and 5 services
One server that thinks like a marketer.
Agentcy eliminates all three walls. Every marketing data source. One set of tools. Insights, not JSON.
Answers, not JSON
Agentcy synthesizes results server-side before returning them. You get trends, anomalies, and specific next steps — not raw API payloads. No other marketing MCP server does this. We checked every one on GitHub.
4 tools. 19+ sources and growing.
Every data source lives behind the same compact set of MCP tools. New sources never add tool definitions. Your context window stays clean no matter how many sources we add.
One portal. Every client.
Add a domain, connect your data sources once, and switch between clients instantly. One domain links your GA4 property, Ads account, Search Console site, and everything else. No property IDs to remember, no config files to edit.
One connection beats a dozen separate tools
Other approaches require a separate tool for each data source — GA4, Ads, Search Console, YouTube. Agentcy gives you everything through one connection, keeping your AI fast and focused.
Less room for your actual questions
agentcyresearchlist_sourcesget_current_dateVirtually all capacity free for your questions
Claude Code warns when you exceed 40 tools. A single GA4 MCP can define 54. Agentcy gives you 19+ data sources through 4 tools — and every query returns ~700 tokens of synthesized insight instead of 5,000–25,000 tokens of raw JSON. Less overhead and less waste on every single question.
One question. Multiple sources.
With separate tools, cross-source queries mean multiple JSON dumps — 24,000+ tokens of raw data your AI has to correlate itself. Agentcy routes to all sources internally and returns one synthesized answer — 94% fewer tokens, with recommendations built in.
How is our ad spend performing relative to actual store revenue? Are we getting a return?
$6,775 in store revenue from 15 orders — but only $13 attributed to ads. Average order value: $226.
$900 spent across 2 active campaigns, 347 clicks — but ROAS is 0.01x. Honeycomb campaign ate 68% of budget.
Store revenue is strong but ads aren't driving it. Conversion tracking is likely broken — 25 conversions recorded but almost no revenue attributed.
Your store is generating $6,775/month but Google Ads contributed only $13 of it — a net loss of $887. Your Honeycomb Containers campaign recorded 24 conversions but nearly zero revenue, which signals broken conversion tracking. Pause both campaigns immediately, fix your purchase event tracking in Tag Manager, then relaunch with ROAS bidding targeting 4x.
One question, one answer. ~1,000 tokens of synthesized insight instead of 24,000+ tokens of raw JSON.
The proof is in the data.
Real benchmarks. Real savings. Every number independently verified against competing MCP servers.
vs. raw JSON from competing MCP servers
in a typical 3-question marketing session vs. separate MCP servers
context window protection vs. separate servers
behind 4 MCP tools — growing every month
from signup to your first answer
Benchmarked against real API responses from GA4, GSC, Google Ads, and WooCommerce — same endpoints, same data, same date ranges. Tool definition counts verified from published MCP servers on GitHub.
Stop fighting your tools.
Start getting insights.
No more raw JSON. No more context window math. No more editing config files between clients. Just ask your question and get an answer.
Free tier · No credit card required · 50 queries/month