How to evaluate cloud integration platforms for AI agent access

Most cloud integration platforms were built for a world where systems talked to each other in batch jobs and webhooks. Now you're being asked to evaluate them for a different job: giving AI agents reliable, authenticated access to the things your product actually does. The criteria are not the same.

This guide walks through a structured evaluation. By the end, you'll have a scorecard you can run against any cloud integration platform — iPaaS, embedded iPaaS, MCP gateway, or tools platform — and a clear view of where each one fits and where it breaks. Prerequisites: a shortlist of two or three platforms, access to one of your product's API specs, and about two hours.

Step 1 — Frame the job before you score anything

Before you compare features, write down the job. Cloud integration platforms historically solved system-to-system data movement: Salesforce to NetSuite, HubSpot to a data warehouse, an ERP to a billing tool. The buyer was usually IT. The user was usually a workflow, not a person.

Agent access is a different job. The caller is non-deterministic. The action runs as a specific authenticated user. The surface needs to cover what your product can do, not just what its public API documents. If the integration software you're evaluating was designed for the first job, it will struggle at the second — not because the vendor is bad, but because the architecture assumes things that no longer hold.

Write a one-paragraph job statement. Two sentences. Pin it above your scorecard. Every criterion below ladders back to it.

Step 2 — Map the categories so you're comparing like with like

The phrase "cloud integration platforms" covers at least five categories that behave very differently when an agent is the caller. Sort your shortlist before you score.
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If two vendors on your shortlist sit in different rows, you're not running a comparison — you're running two separate evaluations. Either narrow the list or split the scorecard.

For more on where each layer sits in the broader stack, see the agent stack: a map for platform teams.

Step 3 — Score on capability coverage, not connector count

Vendor pages lead with connector counts. "500+ pre-built connectors." Ignore the number. Ask a different question: for one product you actually need to expose to an agent, how much of what that product can do is reachable through the platform?

Pick one product. Write down ten things a user can do in the UI that an agent would plausibly need to do. Now check each against the platform under evaluation.

• For traditional iPaaS: how many of the ten map to actions the platform exposes? In most cases, it's the CRUD-heavy ones. The workflow actions, the multi-step UI operations, the permission-sensitive ones — those usually aren't there.
• For embedded iPaaS: the question reverses. Does it expose your product out to agents, or does it pull other systems into your product? Most embedded iPaaS vendors do the second.
• For an MCP gateway: how many of the ten exist as MCP tools on a server you'd run? The gateway doesn't make tools — it governs them. You still need the tools.
• For a tools platform: how many of the ten can it generate from your existing codebase or API surface? This is the right question to be asking, even if the answer needs work.

Score each platform out of ten. This is the most important number on your scorecard. We've written more on the underlying gap in your APIs expose 2% of what your product can do.

Step 4 — Test authentication and identity propagation

This is where evaluations usually fall apart, and where the gap between platform integration for workflows and platform integration for agents is widest.

Ask the vendor a specific question: when an agent invokes a tool through your platform on behalf of an end user, whose credentials does the downstream API see?

There are three honest answers:

• A shared service account. Common. Easy to set up. Wrong for almost every enterprise agent use case — audit trails, row-level security, and per-user permissions all collapse.
• A bring-your-own token pattern. The agent passes a user token, the platform forwards it. Works, but you're on the hook for token lifecycle.
• Managed per-user auth with token refresh and revocation. The platform handles OAuth, holds the tokens, and executes calls as the authenticated user. This is what production agents need.

If the platform only supports the first answer, it's an automation tool with AI marketing on top. Score accordingly.

Step 5 — Stress-test the maintenance model

Integration software ages. APIs change. Products ship features. The question is who pays the maintenance cost and how often.

Ask three concrete questions:

1. When the underlying API adds a field, how does the platform pick it up? Manual update by your team? Vendor-side update on a release schedule? Automated scan against the codebase?
2. When the underlying API changes a contract, how do you find out? Silent breakage in production, or pre-deployment signal?
3. When you add a new product to your portfolio, what's the path to exposing it?

For traditional iPaaS, the answer to (3) is usually "wait for a connector or build a custom one." For embedded iPaaS, the question doesn't apply cleanly. For a tools platform that generates from your codebase, the answer should be "point it at the new repo."

This is the dimension that determines five-year cost. Score it.

Step 6 — Check observability and failure handling

Agents fail differently than workflows. A workflow fails on a schema mismatch and pages someone. An agent fails on a tool call and retries with a slightly different argument, three times, before giving up. By the time you notice, you've burned tokens and confused the user.

Evaluate:

• Per-tool-call logs with input, output, latency, and caller identity.
• Distinguishable error types (auth failure vs rate limit vs upstream 500 vs validation error). Generic 500s back to the agent are unusable.
• Rate limit handling at the platform layer, not pushed down to the agent.
• An audit trail that ties every tool call back to the authenticated user.

If the platform's observability story is "we log requests," it was built for a different job.

Step 7 — Run the build, buy, or wait check

Before you commit to any platform, run the same shortlist past the three options every team in this position actually has: rebuild the API layer, build bespoke connectors, or buy a platform that generates tools against what exists.

The trap is treating "buy" as one option. It's at least three, because the categories in Step 2 solve different problems. A traditional iPaaS purchase doesn't substitute for a tools platform. An MCP gateway doesn't substitute for the tools the gateway is governing.

We walk through the trade-offs in API modernisation for agents: build, buy, or wait. The short version: rebuilding takes years, bespoke connectors don't compound, and "buy" only works if the platform you buy is solving the access problem rather than an adjacent one.

Common pitfalls

Counting connectors. The number is a marketing artefact. Coverage of one product matters more than breadth across five hundred.

Treating MCP support as a category. "MCP-native" tells you the protocol the platform speaks. It tells you nothing about whether the tools exist, whether they cover what your product can do, or how they're maintained. Protocol is the easy part.

Skipping the auth conversation. Service-account integrations look fine in a demo and break the first time a customer asks how an action was attributed.

Evaluating against today's agent project. The platform you pick has to hold up across the next three products you ship agents on. Evaluate against the portfolio, not the pilot.

Confusing embedded iPaaS with agent access. Embedded iPaaS primarily wires third-party tools to your product for your customers' use. Agent access exposes your product's capabilities out to agents. Different orientation, different platform.

If your shortlist still has two platforms after this scoring exercise, run the Step 3 capability test on a second product. The platform that holds up across both is the one to pilot.