Ask ten martech vendors if their AI agents support “open interoperability” and nine will say yes. Ask them to explain what that means at the protocol level, and watch the room go quiet. AI agent interoperability has become the new checkbox on RFPs, but most buyers can’t tell a genuine Model Context Protocol integration from a marketing slide.
That gap is expensive. Gartner has flagged agentic AI as one of the fastest-moving categories in enterprise software, which means the vendors you sign this quarter will either plug cleanly into next year’s agent ecosystem or force a costly rebuild. Understanding what MCP and A2A actually do — not what the sales deck implies — is now a procurement skill, not a technical curiosity.
What MCP and A2A Actually Are
Strip away the acronyms and you’re left with two fairly simple ideas.
Model Context Protocol (MCP), introduced by Anthropic, standardizes how an AI agent connects to external tools, data sources, and systems. Think of it as a universal adapter. Instead of building a custom integration every time an LLM needs to query your CRM, pull inventory data, or read a Google Sheet, MCP gives developers one consistent way to expose that data to any compliant agent. If your martech vendor says their AI agent “supports MCP,” it means their tool can act as a server that other agents — including ones your team builds internally — can plug into without custom middleware.
Agent2Agent (A2A) Protocol, backed initially by Google and now under the Linux Foundation, solves a different problem: how agents from different vendors talk to each other. MCP connects an agent to tools and data. A2A connects agent to agent. If your campaign-planning agent needs to hand a task to your ad-buying agent from a completely different vendor, A2A is the handshake protocol that makes that possible without a brittle point-to-point integration.
MCP is about an agent reaching into your systems. A2A is about your agents reaching each other. Confusing the two is the fastest way to buy the wrong capability.
Both protocols matter because the alternative — proprietary, closed integrations — is exactly what’s been strangling martech stacks for a decade. We’ve covered this shift in more depth in how these protocols decide your stack’s fate, but the short version: closed ecosystems win short-term deals and lose long-term flexibility.
Why This Suddenly Matters for Marketing Teams
Six months ago, “AI agent” mostly meant a chatbot with a system prompt. Now it means something that can independently query your CDP, draft a media plan, negotiate a programmatic bid, and log the outcome in your CRM — all without a human clicking through five different dashboards.
That autonomy is the entire value proposition. It’s also the entire risk. An agent that can write to your CRM without a governance layer is a liability, not a feature — a point we’ve detailed in the CRM write-access governance checklist. Interoperability standards like MCP and A2A aren’t just technical nice-to-haves. They’re the plumbing that determines whether your agents operate inside a controlled, auditable framework or as a patchwork of one-off API keys nobody fully documented.
There’s a commercial angle too. Vendors that build on open protocols are implicitly betting they can win on product quality rather than lock-in. Vendors that build closed, proprietary agent frameworks are betting the opposite. Neither approach is inherently wrong, but you should know which bet you’re funding before you sign a two-year contract.
The switching-cost problem nobody puts in the deck
Here’s the uncomfortable math: if your AI-powered attribution tool, your creator-matching platform, and your ad-buying agent all use proprietary connectors, replacing any one of them means rebuilding every integration touching it. Multiply that across a stack with a dozen AI-enabled tools and you’ve got a switching cost that quietly locks you in for years — often without anyone on the finance side realizing it happened.
Open protocol support flips that math. If three vendors in your stack all speak MCP, swapping one out becomes a configuration change, not an engineering sprint. That’s the practical, boring, extremely important reason interoperability belongs in your vendor scorecard.
What “Support” Actually Means (And What It Doesn’t)
This is where vendors get slippery. “We support MCP” can mean anything from “we’ve fully implemented the spec and pass conformance tests” to “one engineer built a proof-of-concept in a hackathon eight months ago and it’s still on the roadmap.”
Ask these questions before you take the claim at face value:
- Is it a server, a client, or both? A vendor might expose an MCP server (letting your agents query their data) without being an MCP client (letting their agents query your other tools). You often need both directions.
- Which A2A capabilities are implemented? A2A defines task delegation, streaming updates, and capability discovery. Partial implementations can handle simple handoffs but choke on multi-step workflows.
- Is there a public changelog or spec version reference? Both protocols are evolving quickly. A vendor stuck on an early spec version may not support features you’ll need in six months.
- Can you test it yourself? Any vendor confident in their implementation should let you run a sandbox integration before contract signature, not after.
We built a more granular version of this vetting process in our interoperability audit for martech vendors, which is worth running before any AI-heavy renewal conversation.
A Quick Gut-Check: The Creator and Campaign Stack
Nowhere is this more relevant right now than in the creator economy tools brands rely on daily. Creator-matching platforms increasingly claim “AI agent” capabilities — auto-sourcing influencers, drafting outreach, negotiating rates. If those agents can’t hand off structured tasks to your CRM or reporting stack via a real protocol, you’re stuck manually re-entering data, which defeats the entire point of automation.
Our analysis of creator-matching platforms and protocol support found a wide gap between platforms that treat interoperability as core architecture versus those bolting it on for a press release. The tell is usually in the documentation: real implementations publish technical specs; marketing implementations publish blog posts.
If a vendor’s only proof of MCP or A2A support is a press release rather than a developer doc, treat the claim as aspirational, not operational.
Adoption Is Moving Faster Than Most Procurement Teams Realize
The adoption curve here isn’t gradual. Since MCP’s release, thousands of community and enterprise MCP servers have appeared, and major platforms — from Slack to Notion to Salesforce-adjacent tools — have added support within a single product cycle. A2A adoption, while newer, jumped considerably once it moved under Linux Foundation governance, which signaled to enterprise buyers that it wasn’t a single-vendor lock-in play in disguise.
We tracked the pace of this shift in current MCP and A2A adoption rates, and the pattern is clear: vendors serving enterprise or B2B buyers are adopting faster than consumer-facing tools, largely because enterprise procurement teams are now asking these questions directly in RFPs. If your vendor evaluation checklist doesn’t include protocol support yet, you’re behind buyers who compete for the same budget line.
This isn’t just a martech phenomenon, either. Analysts at Gartner and Forrester have both flagged agent interoperability as a top infrastructure risk category for enterprise AI programs going forward, and research groups like eMarketer have started tracking martech vendor AI claims against actual implementation depth. The scrutiny is catching up to the hype.
Building an Evaluation Framework That Doesn’t Rely on Vendor Claims
You don’t need a computer science degree to vet this properly. You need a checklist and the discipline to insist on proof, not promises.
- Request the spec version and conformance test results. Legitimate implementations can produce this in a day. Vague implementations take weeks and still won’t produce anything concrete.
- Map your existing stack’s protocol status. You likely already own tools with partial MCP or A2A support. Know which ones before adding a new vendor into the mix.
- Test a real handoff scenario in a sandbox. Don’t take a demo at face value — simulate a task delegation between two systems and watch what breaks.
- Score readiness, not hype. A structured framework beats a gut feeling. The agentic AI readiness score framework is a solid starting point for scoring vendors against your actual operational maturity, not theirs.
- Build in a kill switch requirement. Any agent with autonomous write access to your systems needs an emergency stop clause in the contract — a requirement now showing up explicitly in kill-switch standards checklists procurement teams are adopting.
None of this is about distrusting every vendor pitching AI agents. It’s about recognizing that “interoperable” is a technical claim with a technical answer, and treating it as a soft marketing term is how brands end up rebuilding their stack eighteen months from now under deadline pressure.
The Bottom Line for Budget Owners
Interoperability isn’t a feature you buy once. It’s an ongoing architectural bet on how flexible, auditable, and future-proof your martech stack remains as agentic AI matures. Vendors who can prove real MCP and A2A support — with documentation, sandbox access, and conformance evidence — are giving you optionality. Vendors who can’t are asking you to trust a black box with production data and budget authority.
Next step: before your next vendor renewal or RFP cycle, require a live sandbox test of any claimed MCP or A2A integration. If they can’t produce one within a week, you have your answer.
Frequently Asked Questions
What is the difference between MCP and A2A protocol?
MCP (Model Context Protocol) standardizes how an AI agent connects to external tools and data sources, like a CRM or CDP. A2A (Agent2Agent Protocol) standardizes how separate AI agents communicate and delegate tasks to each other. MCP is agent-to-tool; A2A is agent-to-agent.
Why does protocol support matter when choosing a martech vendor?
Vendors with genuine MCP or A2A support let you swap tools or integrate new ones without custom engineering work. Vendors relying on proprietary, closed integrations create switching costs that quietly lock you into their platform, regardless of performance.
How do I verify a vendor’s interoperability claims instead of just trusting the sales pitch?
Ask for the specific protocol version they’ve implemented, request conformance test results, and insist on a sandbox environment where you can simulate a real task handoff before signing a contract.
Is MCP or A2A support required for AI agents to work at all?
No. Agents can function using proprietary APIs and custom integrations. The protocols aren’t a functional requirement — they’re a flexibility and risk-mitigation requirement that protects you from vendor lock-in and integration debt.
Which martech categories are adopting these protocols fastest?
Enterprise-facing categories, including CRM-adjacent tools, ad-buying platforms, and creator-matching platforms serving B2B buyers, are adopting faster than consumer-facing tools, largely driven by procurement teams asking direct questions during RFPs.
Frequently Asked Questions
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