MCP vs REST for AI Agents: Why You Probably Don't Have to Choose

You probably don't have to choose

If you run ads and you want an AI assistant to do the heavy lifting, here is the short version. You connect Xylo to your AI app once, and from then on you just talk to it. "Launch a Reels campaign." "Why is my cost per purchase up this week?" "Send me the Friday report across Meta, Google, and TikTok." The plumbing underneath is called MCP, and your AI agent handles it for you. You never see it.

So why does this article compare MCP and REST at all? Because there are two ways software can connect to Xylo, and the difference matters if you are a developer wiring up your own system. For everyone else, the choice is already made. Your AI app speaks MCP, that is the path we recommend, and the rest of this post explains why in plain language before getting into the developer details near the end.

Xylo is the connector that lets Claude, ChatGPT, Cursor, Claude Code, Codex, or any MCP compatible AI agent work directly inside your Meta, Google, and TikTok ad accounts in plain English. Tagline: hand your ad accounts to an AI agent. Hours of account work, done in a sentence.

What MCP and REST actually are

Think of REST as a set of street addresses. Each address is a specific endpoint (list campaigns, update a budget, pull yesterday's insights). To use them, something has to know every address in advance, knock on the right door, and bring the right paperwork. That something is usually code a developer writes.

MCP, the Model Context Protocol, is different. Instead of memorizing addresses, your AI agent asks Xylo "what can you do?" and gets back a live menu of capabilities, each with a description and the exact inputs it accepts. The agent reads the menu, picks the right capability for what you asked, and calls it with checked inputs. No memorized addresses, no guesswork.

That single difference (a memorized map versus a live menu) is what makes MCP the natural fit for an AI agent, and REST the natural fit for hand written software.

The everyday path: MCP through your AI app

Here is the whole setup, start to finish.

1. Connect in about a minute. Sign in, authorize Meta, Google, or TikTok through their normal OAuth screens, and pick your account. Your access tokens are encrypted (AES-256). The AI agent never sees your credentials.
2. Ask in plain English. No dashboards, no CSV exports, no glue code. You talk to your AI app the way you would talk to a media buyer.
3. Xylo does the work. The agent uses 300+ read and write ad operations across Meta, Google, and TikTok to do the actual work, then reports back what it changed.

Point your AI app at the Xylo MCP server once, at https://xylomcp.com/api/mcp, and you are connected. It works with Claude (on claude.ai or Claude Desktop, through Connectors), ChatGPT (any paid plan, on the web, in Developer mode), Cursor, Claude Code, Codex, and anything else that speaks MCP.

After that, you are just talking. Real examples you could type today:

Launch a paused Reels campaign on Meta for the spring sale, $40 a day, target women 25 to 44 in the US, and show me the ad set before anything goes live.

Why is my cost per purchase up this week? Check Meta, Google, and TikTok and tell me which campaigns moved.

Pause any ad set whose frequency is over 4 and tell me exactly what you changed.

Build me one report across all three platforms for last month, sorted by return on ad spend.

The agent figures out which tools to call, calls them, and answers. For more ideas on what to say, browse our prompt library.

Why MCP is the better fit for AI agents

A few practical reasons, in the order they tend to matter.

The agent discovers what it can do, live. With REST, software has to be told the full list of endpoints up front, usually pasted into a prompt or hard coded. Add a new capability and someone has to update that list. With MCP, the menu of tools is delivered the moment your AI app connects. New capabilities show up automatically. The agent literally cannot call something that does not exist.

Inputs are checked before anything happens. Every MCP tool publishes exactly what it accepts (which fields, which allowed values). If your agent tries to set an impossible status or a misspelled field, that is caught before the request is ever sent. With REST, a wrong guess fails only after the call goes out, and the agent has to interpret the error and try again.

Safety is built in. New campaigns are created paused by default, so nothing spends until you approve it. You stay the decision maker. The agent proposes, you confirm, and only then does money move.

One agent, three platforms. You do not stitch Meta, Google, and TikTok together yourself. The agent works across all three and can produce a single, normalized cross-platform report, so "compare my return on ad spend everywhere" is one sentence, not three exports and a spreadsheet.

The fiddly stuff MCP quietly handles

These are the things that used to eat an afternoon. With Xylo plus your AI agent, you never touch them.

Errors that explain themselves. Raw ad platform errors are famously cryptic. MCP returns results and errors in the same clean, agent readable shape, so when something is rate limited or needs a moment, the agent understands the message and acts on it instead of stalling.

Memory across a conversation. Ask "pause the worst performer" right after "show me last week's campaigns," and the agent already has the list in front of it. It knows which campaign you mean. There is no separate system you have to build to remember context between steps.

Logins and tokens, out of sight. Authorization happens once, server side, and your tokens stay encrypted. The agent does the work without ever holding your credentials.

Here is the contrast in the terms you actually care about.

What you care about	REST API (developer path)	MCP (your AI app)
Who sets it up	You write code	Your AI app, in about a minute
Picking the right action	You program every call	The agent reasons and picks
Catching mistakes	After the request fails	Before the request is sent
Multi-step work	You store the context	It stays in the conversation
Logins and tokens	You manage keys	Handled server side, encrypted
Multiple platforms	You stitch the calls together	One agent across Meta, Google, TikTok

When developers reach for REST instead

REST is the developer option, and it is a good one for the right job. Reach for the Xylo REST API when:

• You are building a fixed pipeline. If your software runs the same sequence of steps every night (pull yesterday's campaigns, pull insights, email a report), a deterministic script is simpler and more predictable than dynamic reasoning.
• You want full control of each request. REST hands you every header, query parameter, and field directly. If you need precise, custom behavior, that control is yours.
• Your system is purely server side. A backend service that calls an API on a schedule does not need an AI agent in the loop at all.
• You want maximum portability. REST works from any language with an HTTP client, with no MCP support required.

Most teams end up using both. They let people run day to day work by chatting through MCP, and they wire up REST for the scheduled, behind the scenes jobs.

For developers: the REST shape

This section is optional and exists only if you are writing code. Everyone else can skip it.

The base URL is https://api.xylomcp.com. Authenticate with an x-api-key header (keys look like xy_sk_...). Most Meta endpoints also need an x-ad-account: act_... header. Google needs x-google-customer-id, and TikTok needs x-tiktok-advertiser-id. Meta endpoints live under /v1/..., Google under /v1/google/..., and TikTok under /v1/tiktok/.... A typical call:

curl https://api.xylomcp.com/v1/campaigns \
  -H "x-api-key: xy_sk_..." \
  -H "x-ad-account: act_123456789"

Responses come back as { data, meta, paging? }. Budgets are in dollars, not cents. New campaigns default to paused for safety. Results are cached with a short time to live, and you can pass ?refresh=true to bypass the cache. Under the hood Xylo talks to Meta Graph API v25.0, Google Ads API v23, and TikTok Marketing API v1.3, so you never have to track those versions yourself. Full details are in the API documentation.

Both run on the same engine

You are not choosing between two different products. MCP and REST sit on top of the same Xylo platform, the same data normalization, the same caching, and the same safety defaults. When your AI agent does something through MCP, it reaches the same place your code would reach through REST. So you can run your interactive, plain English work through your AI app and your scheduled jobs through REST, and the numbers always line up.

That is the real answer to "MCP or REST?" For almost everyone, the agent uses MCP and you simply talk to it. For developers with a specific automation to build, REST is there. Either way, it is one platform underneath.

Getting started

1. Create a free Xylo account. No credit card, and the free tier includes the full MCP server plus REST API.
2. Connect Meta, Google, or TikTok and pick an account. Tokens are encrypted and the agent never sees them.
3. Point your AI app at https://xylomcp.com/api/mcp and ask it about your campaigns.

For a deeper look at the protocol itself, read our MCP protocol explainer. For hands on examples of letting an agent run your accounts, see building AI agents for ads.

Connect Xylo to your AI agent, start on the free tier, and hand your ad accounts a capable assistant. No card required.