Every marketing team we talk to has the same story. They connected a free GA4 MCP server to Claude or Cursor, asked "how's my organic traffic doing?" — and got 12,000 tokens of raw JSON back. Nested dimensionValues, repeated TYPE_INTEGER headers, property quota objects nobody will ever look at.
The LLM dutifully reads all of it, burns another 2,000 tokens reasoning about it, and gives a mediocre answer. Because raw data isn't insight. And an LLM with no marketing context doesn't know what "good" looks like.
That "free" MCP server just cost $0.11 in tokens and returned zero recommendations.
Today we're launching Agentcy to fix this.
The problem nobody talks about
The MCP ecosystem is booming. There are servers for GA4, Search Console, Google Ads, Meta Ads, Shopify, and dozens more. Each one does the same thing: wraps an API and dumps the raw response into your context window.
This creates three compounding problems:
Token bloat. A single GA4 detailed analysis returns ~25,000 tokens of JSON. A Search Console query adds another ~8,500. Google Ads, ~9,000 more. Your context window fills up fast, and you're paying for every token.
Tool sprawl. Each MCP server adds 5-10 tool definitions to your context. Three servers means ~20 tools and ~1,269 tokens of overhead — loaded on every conversation, whether you use them or not. Add a full marketing stack — GA4, Search Console, Google Ads, HubSpot, Shopify, and a web search tool — and you're looking at 149 tools and 139,575 tokens before the conversation even starts.
Zero synthesis. Raw JSON from an API doesn't contain recommendations. It doesn't correlate data across sources. It doesn't know that a 23% bounce rate increase on your pricing page is worth investigating. Your LLM has to figure all of that out from scratch, every single time — and it usually gets it wrong.
Our approach
Agentcy is one MCP server that replaces all of them. You ask a question in plain English. You get back an insight, not a data dump.
You: "How is organic traffic performing and which pages are driving growth?"
Agentcy: Organic sessions increased 12% month-over-month, driven primarily
by 3 new pages ranking in positions 3-7 for high-intent keywords.
Your /pricing page saw a 23% bounce rate increase — consider
testing the hero section. Top recommendation: create supporting
content for your top-ranking /guide page to consolidate the
topic cluster.
Behind the scenes, Agentcy routed to GA4 and Search Console, executed the API calls in parallel, and synthesized the results with marketing domain expertise. The LLM didn't have to figure any of that out.
The key architectural decision: Agentcy's tool count stays at 4 whether we have 4 data sources or 500. Routing, selection, and coordination all happen server-side. Six common marketing MCP servers consume 149 tool definitions and 139,575 tokens. Every new Agentcy service costs zero additional tokens — it's already behind the same agentcy tool. Four tools. ~587 tokens. Nineteen data sources.
The numbers
We benchmarked Agentcy against the raw JSON MCP servers people are actually using. These aren't estimates — they're measured.
Token savings
| Data Source | Raw JSON (Other MCPs) | Agentcy | Savings |
|---|---|---|---|
| GA4 (typical report) | ~5,000 tokens | ~1,000 tokens | 79% |
| GA4 (detailed analysis) | ~25,000 tokens | ~1,200 tokens | 95% |
| Google Search Console | ~8,500 tokens | ~1,200 tokens | 86% |
| Google Ads | ~9,000 tokens | ~1,200 tokens | 87% |
| Web Research (17 engines) | ~22,000 tokens | ~5,600 tokens | 75% |
Combined across the Google marketing stack: up to 94% fewer tokens.
What those tokens cost
At Claude Sonnet pricing ($3/$15 per million tokens), a single detailed GA4 query:
- Raw JSON MCP: ~25,000 input + ~2,000 output = $0.11 per query
- Agentcy: ~1,200 input + ~200 output = $0.006 per query
That's 18x cheaper per query. Run 50 queries a day across a few clients and you're saving $150+ per month on LLM costs alone — before counting the time you save reading actual insights instead of scrolling through JSON.
The overhead you don't see
Tool definitions load on every conversation — even when you ask about movies. With 6 marketing MCP servers installed, you pay 139,575 tokens before you type a single word.
Per-first-message cost at full price, tool definitions only:
| Model | 6-MCP Stack | Agentcy |
|---|---|---|
| Claude Opus 4.6 ($5/M) | $0.70 | $0.003 |
| Gemini 3.1 Pro ($2/M) | $0.28 | $0.001 |
| GPT-5.2 ($1.75/M) | $0.24 | $0.001 |
Scale that to a month of conversations:
| Usage Level | Convos/Day | MCP Stack (Opus) | Agentcy (Opus) |
|---|---|---|---|
| Solo marketer | 5 | $104.70/mo | $0.44/mo |
| Small agency | 20 | $418.80/mo | $1.76/mo |
| Large agency | 50 | $1,047.00/mo | $4.39/mo |
"But caching fixes this." Partially. All three providers auto-cache tool definitions after the first message. But the first message of every new conversation is always full price. And caching reduces cost — it doesn't reduce context window consumption. Those 139,575 tokens still occupy space in the window regardless. Your AI has less room for actual work either way.
Quality difference
| Agentcy | Raw JSON MCPs | |
|---|---|---|
| Actionable recommendations per response | 8-12 | 0 |
| Marketing domain expertise | Built in | None |
| Cross-source correlation | Automatic (1 query) | Manual (3-5 round-trips) |
| Tool overhead | 4 tools / ~587 tokens | 149 tools / 139,575 tokens |
What's live today
Nineteen data sources are available right now:
- Google Analytics 4 — 14 operations covering reports, metadata, audiences, and validation
- Google Search Console — 12 operations for search analytics, URL inspection, and sitemaps
- Google Ads — 12 operations for campaign reporting, keyword intelligence, and GAQL queries
- YouTube Analytics — 7 operations for channel, video, and audience performance
- Google Tag Manager — 8 operations for container, tag, trigger, and variable management
- Google Sheets — 6 operations for reading, querying, and analyzing spreadsheet data
- WooCommerce — 12 operations for orders, products, sales, inventory, and refund analysis
- Research & Web Intelligence — 100+ search engines, webpage scraping, and YouTube transcripts
- SpyFu — Competitor keyword research, PPC analysis, and domain comparison
- HubSpot — CRM contacts, companies, deals, tickets, email campaigns, and pipeline analytics
- PageSpeed Insights — Core Web Vitals and performance audits
- DNS Lookup — DNS record inspection and health checks
- WHOIS / RDAP — Domain registration and ownership data
- Sitemap Analysis — Sitemap parsing and coverage analysis
- Schema Markup — Structured data validation and recommendations
- Readability Analysis — Content readability scoring and improvement suggestions
- Technology Detection — Website technology stack identification (3,000+ signatures)
- Image Generation — AI-generated marketing visuals and creative assets
- Data Visualization — AI-generated charts, graphs, and visual data representations
Every source works through the same natural language interface. Ask a question that spans GA4 and Search Console, and Agentcy handles the routing and synthesis automatically.
The research tool works without any domain or credentials — search across 100+ engines, read any webpage, pull YouTube transcripts. Competitor analysis, market research, and content gap identification all from the same server.
What's next
We're porting integrations from our production agency platform — the same system that runs 20+ client accounts today. Coming soon:
- Meta Ads — Facebook and Instagram campaign performance
- Semrush / Ahrefs — Rank tracking, keyword research, backlink analysis
- Shopify — Store analytics, product performance, customer data
- LinkedIn Ads, TikTok Ads, Pinterest Ads, Microsoft Ads — Full ad platform coverage
Every new service is available to all Agentcy users instantly. No new config, no new auth flow, no new tool definitions. You just ask a question and the new data source is there.
Built for agencies
If you manage multiple client accounts, Agentcy was designed for you. Every tool call takes a domain parameter — switch between clients by changing one string.
"Show me organic traffic for aurora-fitness.com"
"Now compare northpeak-outdoor.com's ad performance"
"What's the WooCommerce revenue trend for velvet-roasters.com?"
No reconfiguring. No switching servers. No juggling API keys. All credentials are managed in the portal, not scattered across MCP config files.
Getting started
Five minutes from signup to your first insight:
- Create an account at app.goagentcy.com
- Connect your data sources (each is one click in the portal)
- Add your domains
- Copy the MCP config into your client:
{
"mcpServers": {
"agentcy": {
"command": "npx",
"args": ["-y", "@agentcymcp/server"],
"env": {
"AGENTCY_API_KEY": "agcy_your_key_here"
}
}
}
}
- Ask a question
That's it. Works with Claude Code, Claude Desktop, Cursor, VS Code, ChatGPT, Windsurf, and any other MCP-compatible client.
We offer a free tier (50 queries/month, unlimited domains) so you can try it without commitment. When you're ready, plans start at $29/month — still cheaper than what the "free" MCP servers cost you in hidden tokens.