How Relay.app's MCP Integration Powers Virtual Marketing Analytics Servers

I've been testing something unconventional with marketing analytics lately, and it's changing how I think about AI agents for marketers.

Most teams I speak with are either building general-purpose AI agents that try to do everything, or they're manually wrangling data from Google Analytics, PostHog, and Microsoft Clarity every time they need campaign insights. Both approaches miss the point. The first creates context bloat and security nightmares. The second wastes hours that could be spent optimising campaigns instead of extracting data from multiple dashboards.

There's a better way: Virtual MCP servers that solve specific marketing problems, and Relay.app's MCP support makes building them surprisingly practical.

The MCP Security Problem Nobody Talks About

Model Context Protocol exploded in adoption after Anthropic released it in November 2024. David Soria Parra and Justin Spahr-Summers built it to solve the "M×N problem" - the combinatorial explosion of connecting M different AI models with N different tools. Within months, OpenAI and Google adopted it, and by early 2025, the protocol was seeing over 8 million weekly SDK downloads.

But here's what the hype cycle ignored: every MCP tool you connect to your AI agent is a potential security vulnerability.

Security researchers identified multiple critical issues within months of MCP's release. Microsoft found MCP servers running in production with direct database access and weak authentication. Tool poisoning attacks let malicious instructions hide in tool descriptions. OAuth token theft could grant attackers access to entire marketing stacks. One vulnerability (CVE-2025-49596) allowed remote code execution.

The core problem isn't the protocol itself - it's how teams implement it. When you connect a general-purpose AI agent to 15 different MCP servers spanning your entire marketing stack, you're creating what security professionals call a "keys to the kingdom" scenario. Compromise one agent, get access to everything.

Why General-Purpose Agents Don't Work for Marketing

When Relay.app added MCP support in their July 2025 update, they positioned it as a way to "invoke specific tools from connected remote MCP servers as part of workflows". The promise was compelling: connect your AI agents to any external service through a standardised protocol.

The reality turned messier than the marketing copy suggested.

I've watched marketing teams try to build "master agents" that handle everything from analytics to customer data to advertising platforms. They connect MCP servers for GA4, PostHog, HubSpot, Google Ads, LinkedIn, Slack, and their CRM. Then they wonder why their agents make incorrect tool selections, expose sensitive customer data in responses, or hit rate limits.

The problem is context bloat. When an AI agent has access to 47 different tools across 12 different systems, it struggles to pick the right one. Each additional tool increases the cognitive load on the model, reduces accuracy, and creates more security attack surface.

But there's a more fundamental issue: most marketers don't need a general-purpose agent. They need specific solutions to specific problems.

Enter Virtual MCPs: Purpose-Built Marketing Automation

We're currently testing a different approach at Growth Method: Virtual MCP servers, sometimes called V-MCPs or MCP gateways.

As the team at Pulse MCP explains in their analysis of virtual MCP servers and gateways, a V-MCP acts as an intermediary layer between AI clients and multiple MCP servers, aggregating and filtering tools to create focused, purpose-specific interfaces.

Think of a V-MCP as a focused agent with access to only the MCP tools needed for one specific marketing task. Instead of connecting directly to GA4, PostHog, Amplitude, and Microsoft Clarity MCP servers, we've built a Marketing Analytics V-MCP that connects to these specific servers behind the scenes and exposes only analytics-relevant functionality.

Here's why this works better:

Reduced Context Bloat: The agent only sees tools relevant to analytics, not your entire marketing stack. This dramatically improves tool selection accuracy.

Security Through Specificity: A Marketing Analytics V-MCP doesn't need tools like create_user or delete_record. By limiting tool access to read-only analytics functions, we've reduced the security blast radius by about 80%.

Better Model Performance: With fewer tools to choose from, the model makes fewer errors and responds faster. We've seen response times drop by 40% compared to general-purpose agents.

Easier Compliance: When you need to audit what data your AI agents can access, reviewing 6 analytics-specific tools is infinitely easier than reviewing 50 general tools across your entire stack.

As Mohammed Mehedi Hasan and his research team noted in their 2025 study of MCP security: "MCP servers are composed of executable code, so users should only use MCP servers that they trust."

The trust problem becomes manageable when you're building purpose-specific agents rather than connecting to random MCP servers from GitHub.

How Relay.app MCP Changes the Game

Relay.app's MCP implementation introduced something most automation platforms haven't: the ability to call remote MCP tools directly within workflow steps using their "Call MCP tool" action in the AI menu.

This matters because it bridges the gap between traditional workflow automation and AI-native architectures. Instead of building complex API integrations or relying on pre-built connectors, you can connect Relay.app agents to any MCP server and access those tools as native workflow steps.

For marketing teams, this means you can build a Marketing Analytics V-MCP once, connect it to Relay.app, and use it across multiple workflows without duplicating effort. Need to pull GA4 traffic data for a weekly report? Use the V-MCP. Want to compare PostHog funnel performance across campaigns? Same V-MCP, different workflow.

The Relay.app MCP integration supports full control over which actions are available in each tool, letting you create granular permissions that align with security best practices. You can create multiple MCP server connections with different permission levels - one for read-only analytics, another for campaign creation, a third for customer data enrichment - and use each only where appropriate.

Building Your First Marketing Analytics V-MCP

The practical implementation is simpler than you'd expect. Here's the framework we follow:

1. Identify the Specific Marketing Problem: Don't start with "I need an AI agent". Start with "I spend 2 hours every Monday pulling campaign metrics from 4 different platforms".

2. Map the Minimum Required Tools: For a Marketing Analytics V-MCP, you might need: get_ga4_traffic, get_posthog_funnels, get_clarity_heatmaps, get_ads_spend. Nothing else.

3. Connect Relevant MCP Servers: Wire up only the external MCP servers needed for these specific tools. In our case: GA4, PostHog, Microsoft Clarity.

4. Add Context-Appropriate Constraints: Set read-only permissions. Limit date ranges. Restrict data access to specific properties or projects.

5. Integrate with Relay.app: Connect your V-MCP to Relay.app using the MCP server configuration, making its tools available as workflow actions.

6. Build Workflows with Human-in-the-Loop: Use Relay.app's approval steps to ensure humans review data before agents act on it.

David Soria Parra, MCP co-creator, emphasised this point in a recent interview: "MCP tries to enable building AI applications in such a way that they can be extended by everyone else that is not part of the original development team through these MCP servers, and really bring the workflows you care about, the things you want to do, to these AI applications."

The key phrase is "workflows you care about" - not every possible workflow.

Real-World V-MCP Workflows in Relay.app

We're seeing marketing teams build Virtual MCPs for specific tasks and orchestrate them through Relay.app workflows:

Weekly Analytics Digest: A workflow triggers every Monday morning, uses the Marketing Analytics V-MCP to pull metrics from GA4 and PostHog, generates a formatted report, and posts it to Slack with an approval step before sharing with leadership.

Campaign Performance Alerts: When ad spend exceeds budget thresholds, the Campaign Performance V-MCP pulls detailed metrics, the workflow pauses for human review, then either adjusts bids automatically or escalates to the marketing director.

Content Performance Tracking: After publishing content, a delayed workflow uses the Analytics V-MCP to check traffic and engagement after 7 days, then creates follow-up tasks in the project management system based on performance.

Competitive Analysis: A weekly batch workflow uses the SEO Monitoring V-MCP to pull ranking changes across multiple competitors, generates a comparison report, and emails it to the content team with priority keywords highlighted.

Each workflow uses Relay.app's human-in-the-loop features to ensure agents never act without oversight on sensitive operations.

The Security Checklist for Relay.app MCP Implementations

Before you connect any MCP server to Relay.app, work through this checklist:

1. Verify MCP Server Authentication: Does your V-MCP use OAuth 2.0 with enterprise identity providers? Static tokens are security risks.

2. Audit Available Tools: List every tool exposed by your MCP server. Remove any that aren't necessary for the specific workflow.

3. Test Data Isolation: Can the MCP server access data from other teams or customers? If yes, fix this before connecting to Relay.app.

4. Configure Relay.app Permissions: Use Relay.app's tool access controls to limit which team members can invoke specific MCP tools.

5. Implement Approval Steps: Add human checkpoints before any workflow executes write operations or shares sensitive data.

6. Monitor Workflow Runs: Review Relay.app's execution logs regularly to spot anomalous patterns or failed tool calls.

7. Rate Limit Workflows: Use Relay.app's scheduling features to prevent runaway automation from overwhelming your MCP servers.

As Microsoft's security team noted in their April 2025 analysis: "98% of reported breaches would be prevented by robust security hygiene and the best protection against any kind of breach is to get your baseline security hygiene right."

What This Means for Marketing Operations

The combination of Virtual MCPs and Relay.app's workflow automation changes how marketing teams should approach AI adoption.

Instead of asking "How do I build an AI agent for marketing?", ask "Which repetitive marketing task costs us the most time?" Then build a focused V-MCP that solves only that problem and orchestrate it through Relay.app workflows that include appropriate human oversight.

This approach scales better too. You can build multiple Virtual MCPs for different workflows without creating the security and complexity nightmares that come with general-purpose agents. Your Analytics V-MCP doesn't need to know about your Lead Enrichment V-MCP. They're isolated systems solving isolated problems, orchestrated through Relay.app's workflow engine.

The future of marketing automation isn't one agent to rule them all. It's a constellation of purpose-built agents, each excellent at one specific task, connected through well-defined interfaces and governed by human-in-the-loop workflows.

Whitney Hazard, marketing lead at Relay.app, observed: "76% of companies use some sort of marketing automation already. It's widely regarded as the future of digital marketing."

But that future only works if we build it securely and deliberately.

Getting Started Tomorrow

Start small. Pick your most time-consuming manual marketing task. Map the minimum MCP tools needed. Build a Virtual MCP that does only that one thing. Connect it to Relay.app and create a workflow that includes human approval before executing any sensitive operations.

For most B2B marketing teams, that first V-MCP should be analytics-focused. You're already pulling data from multiple platforms manually. A Marketing Analytics V-MCP with access only to read-only analytics tools, orchestrated through Relay.app workflows, will save hours every week without exposing your entire marketing stack to security risks.

The paradox of AI agents is that limiting their capabilities often makes them more useful. General-purpose agents are impressive demos. Purpose-built Virtual MCPs orchestrated through proven workflow automation like Relay.app MCP are practical tools that actually ship.