Put your ad data in Claude.

Claude is genuinely useful for media buying now, but how useful depends entirely on one question: can it see your data? Without access to your accounts, Claude is a smart intern with amnesia. With access, it becomes something closer to an analyst who has read every row of your ad history. This guide covers both modes honestly, and how to set up the second one.

Disclosure: I am the founder of Peachblue, which builds one of the tools below. The workflow advice stands regardless of whose tool you use.

What Claude does well with no setup at all

Plenty, actually. Paste in your creative copy and Claude critiques hooks and angles competently. Paste a screenshot of a results table and it reads the numbers. Describe your product and audience and it drafts briefs, generates angle lists, and rewrites headlines in volume. For creative ideation, it is already better than most brainstorm meetings.

The ceiling is just as real:

• It cannot see your accounts. Every number arrives by copy-paste, which means stale snapshots, tiny samples, and no follow-up questions the data could answer.
• Manual data entry invites errors. A pasted table loses the context around it: attribution window, date range, currency, which campaigns were excluded.
• It will reason confidently about numbers it half-remembers. Ask a follow-up two screens later and the model may be working from a garbled version of what you pasted.

Copy-paste Claude is a writing tool. The unlock is making it an analysis tool.

The unlock: MCP

The Model Context Protocol is an open standard that lets Claude call tools that fetch live data. Instead of you pasting numbers in, Claude queries the source and reasons over what comes back. And 2026 is the year the ad platforms embraced it: every one of the big four now ships or has announced an official MCP server. Which sounds like the problem is solved, until you actually try to run all four.

The DIY route: connecting each ad platform to Claude

Here is the current state of the official, platform-run MCP servers, and what each one gives Claude.

Meta ads MCP

Meta launched its official ads MCP connectors in spring 2026, in open beta. Connected, Claude can query the data you would see in Ads Manager: campaigns, ads, spend, and results, for Meta only. It is the platform's raw view: per-ad rows, no creative grouping, no interpretation.

Google Ads MCP

Google shipped its official Google Ads MCP server in April 2026, giving LLMs direct access to the Google Ads API. Same shape: one platform, API-level rows, with Claude left to do the analysis in-chat.

Amazon Ads MCP

Amazon released its Ads MCP server in open beta in February 2026, a connection layer for AI agents into Amazon Ads. Early practitioner writeups note real visibility gaps in what it exposes, and either way the data is raw report rows: no flight pacing math, no creative-level analysis.

TikTok ads MCP

Announced at TikTok World in May 2026, the TikTok for Business MCP server is now live: zero-code setup, hosted endpoints, and explicitly recommended for Claude. It is the most ambitious of the four, exposing roughly 400 tools in full-disclosure mode (a trimmed set of about 40 in progressive mode) that go beyond reporting into campaign creation, bidding, and budget changes. Which makes the shape worth understanding: it is a campaign management surface, handing Claude TikTok's API. Four hundred raw tools is a lot of surface area, and none of it tells Claude which of your creatives is winning or why.

What you end up with

Wire up everything above and this is the stack: four separate connections, four auth flows, four different toolsets with four different vocabularies (one of them 400 tools deep), and each one seeing only its own silo. Claude has to stitch the platforms together by hand in every conversation, reconcile attribution windows that do not match (Amazon DSP reports 14-day only; social platforms differ), and reconstruct basic concepts like "this is the same creative running in nine ads" from scratch, every single time, because raw rows carry no creative identity, no scoring, and no tags. It works, in the way that four spreadsheets and a prayer work.

Or: one connection, with the analysis already done

Peachblue's MCP sits on top of synced, analyzed data across all four platforms instead, and the practical differences stack up fast:

The thread running through every row: answers stay grounded in your performance data and tied to the creative level, which is where scaling decisions actually live. The loop this enables is the one that matters: find the winners, understand why they win, make more of what wins, and verify the next batch against the same score.

Two quieter advantages compound over time. History: Peachblue keeps what it syncs, so analysis is not capped by platform retention limits (Amazon DSP, for instance, only retains about 60 days of report data; your Peachblue history builds forward past it). Context efficiency: tools return ranked, aggregated payloads instead of raw row dumps, so Claude spends its context reasoning rather than arithmetic, which in practice means fewer wrong numbers.

To be fair to the raw option: platform-native MCPs are the right tool for platform-native lookups, and nothing stops you from connecting them alongside Peachblue. The distinction is what you want Claude to be. Raw rows make it a query runner. An intelligence layer makes it an analyst.

Peachblue's server exposes the same 19 tools that power our in-app agent, over your Meta, TikTok, Google Ads, and Amazon DSP data. Everything is read-only; nothing can touch your campaigns.

Setting it up

Prerequisites: a Peachblue account (Pro or higher) with at least one platform synced, and Claude Desktop or Claude Code.

1. In Peachblue, open Settings and go to the MCP tab. Copy your connection URL.
2. In Claude Desktop: Settings, then Connectors, then Add custom connector. Paste the URL.
3. Approve the OAuth sign-in with your Peachblue account when prompted. No API keys.

Full setup details, including Claude Code, are in the MCP docs, and the complete tool list is in the tool reference.

What to actually ask

The queries that earn their keep daily:

• "How did last week compare to the week before, and what drove the change?"
• "Rank my top 10 creatives by composite score this month and tell me what they have in common."
• "Compare my two hero videos head to head. Which one deserves the next budget increase?"
• "Which hook styles are winning in my account right now?"
• "Which headlines are underperforming across my Google RSAs?"
• "What is Reddit saying about my brand this week, and is there an angle worth testing?"

Then the compound move: because Claude holds the whole conversation, you can chain analysis into action. Pull the patterns behind your winners, then in the same thread have Claude draft five new concepts that fit those patterns. Analysis to brief in one sitting, grounded in your own data at every step.

What this replaces, and what it does not

It replaces the export-paste-reformat loop, the "quick question" that used to mean opening four dashboard tabs, and a decent share of weekly report assembly. It does not replace your analytics app for visual browsing, it does not buy or edit media (by design), and it does not replace judgment: Claude with your data is a sharper analyst, not a decision-maker.

Honest limitations: you need a Claude plan that supports connectors, MCP access starts on Peachblue's Pro tier (pricing), and agency workspaces with per-client scoping are coming soon. Fair-use rate limits apply but normal analytical use never meets them.

Where this is heading

Every serious ads tool will expose MCP within a year; the question will shift from "can my AI see my ad data" to "how good is what it sees." Grouped, scored, analyzed data beats raw rows for the same reason a good analyst beats a CSV export. If you want to try it on your own accounts, start a trial, sync a platform, and connect Claude in the time it takes to make coffee. And if you are choosing an analytics layer in the first place, our comparison of the current field is the honest place to start.