Supermetrics alternatives when the consumer is an AI agent, not a spreadsheet
Windsor.ai, Funnel and Improvado all ship MCP servers now. Choose a Supermetrics alternative by who defines the metric, not by connector count.
The right Supermetrics alternative depends on who reads the number. If a person reads it in Looker Studio, a cheaper connector does the job: as of October 14, 2026, Windsor.ai starts at $19 a month billed annually (Windsor.ai) against $39 for Supermetrics (Supermetrics). If an AI agent reads it, the comparison changes. Supermetrics, Windsor.ai, Funnel and Improvado all offer MCP access now, and an MCP server can only pass along a definition of revenue that somebody at your company already wrote down.
Marketing data connector: a tool that pulls metrics from platform APIs (Google Ads, Meta, GA4, TikTok) and delivers them to a destination such as a spreadsheet, Looker Studio, a data warehouse or, since 2026, an AI assistant over MCP. It carries each platform’s definitions as-is. It does not create your company’s.
What criteria should decide the switch?
I’m stating the criteria before the table so you can disagree with them. There are seven:
- Destination. Where the data lands: spreadsheet, BI tool, warehouse, AI client.
- Who defines the metric. The source platform, an admin inside the tool, or a process with an owner and a version history.
- History and retention. How much data is stored, and where.
- Isolation. What the public documentation says about keeping your data separate.
- AI access over MCP. Whether it exists, on which plan, and whether the agent can only read or can also change campaigns.
- Who operates it. Who fixes things when a connector breaks or an API changes.
- Pricing model. Published price, quote, or metered usage.
I left out connector counts and report templates on purpose. All four vendors cover the mainstream ad platforms, and connector count says nothing about the question this article cares about: whether the answer your agent gives matches the one your finance team would give.
What does each alternative do well?
Supermetrics is the shortest path from an ad account to a spreadsheet. Starter and Growth cost $39 and $159 a month billed yearly ($49 and $199 billed monthly), each with one core destination chosen from a list that includes Google Sheets, Looker Studio, Excel, Power BI, Claude and ChatGPT (Supermetrics, checked October 14, 2026). Warehouse destinations, API access and data transformations are listed only on Enterprise, which is quote-based. The MCP server is a separate product for subscribers with API access, and it can create or modify campaigns, which start paused (docs, August 27, 2026).
Windsor.ai is the cheapest option here and the most generous on destinations: every plan sends data to Looker Studio, Sheets, BigQuery and Snowflake, with up to 10 years of history and access to Windsor MCP (Windsor.ai, checked October 14, 2026). Its Claude connector reads and writes to connected accounts, including pausing campaigns and reallocating budget (Windsor.ai).
Funnel is the only one of the four whose pricing page puts business logic on the entry plan. Starter begins at $300 a month billed annually and includes “Semantics: apply your business logic” plus MCP; BigQuery and S3 destinations start at Business, from $600 (Funnel, checked October 14, 2026). Its MCP server is read-only, available on all plans, and includes a get_workspace_context tool that returns the conventions and business rules your admin wrote (Funnel, September 2, 2026). If you’re searching for Funnel.io alternatives because of price, that read-only default is worth weighing before you leave.
Improvado is the closest to a full platform. Its documentation, updated October 6, 2026, describes 46,000+ harmonized metrics, 84 MCP tools, and read and write access (Improvado). There is an MCP-only plan at $100 a month; Advanced and Enterprise are quote-based and include professional services credits (Improvado, checked October 14, 2026).
How do they compare, criterion by criterion?
| Criterion | Supermetrics | Windsor.ai | Funnel | Improvado | Managed data platform |
|---|---|---|---|---|---|
| Destination | 1 core destination on Starter/Growth; warehouse on Enterprise only | All destinations on all plans, including BigQuery and Snowflake | 13 destinations on Starter; BigQuery and S3 from Business | Warehouse, BI and AI clients | Per-client isolated lake; consumed through the client’s AI, API or BI |
| Who defines the metric | Source platform; custom metrics on Enterprise | Source platform | Workspace admin (Semantics) | Harmonized data model plus your team’s rules | Definitions written with your team, versioned, approved by you |
| History | Supermetrics Storage on Enterprise only | Up to 10 years | Storage included; retention not stated on pricing page | In a warehouse you control; rows-per-year cap by plan | Full history for the life of the contract |
| Isolation | Data residency and region control on Enterprise | Not stated on pricing page | Roles, permissions and audit log on Enterprise | Not stated on pricing page; SOC 2 Type II on all plans | Lake isolated per client, on the vendor’s infrastructure |
| MCP | Requires API access; creates and edits campaigns | All plans; reads and writes | All plans; read-only | All plans; reads and writes | Queries already-modeled data |
| Who operates it | You | You | You; SLA support on Enterprise | You, with professional services on quoted plans | The vendor, with a dedicated analyst |
| Pricing | $39–159/mo billed yearly; Enterprise by quote; metered AI credits | $19–499/mo billed yearly; Enterprise by quote | From $300/mo billed annually; Enterprise via sales | MCP Only $100/mo; Starter from $20,000/yr and Growth from $50,000/yr; Enterprise by quote (page updated, checked October 26, 2026) | Monthly, no setup fee, no per-seat charge |
Table sources, all checked October 14, 2026: the official pricing pages of Supermetrics, Windsor.ai, Funnel and Improvado, plus each vendor’s MCP documentation cited above. The right-hand column describes the category; Precisian’s specifics are on its pricing page.
Why is a connector enough for Looker Studio but not for an agent?
Because in Looker Studio there is a person between the number and the decision. Whoever built the report knows that Google Ads counts a purchase up to 30 days after a click by default (Google Ads) and that Meta counts it up to 7 days after a click or 1 day after a view (Meta), so they don’t add the two columns. The agent doesn’t know that. It gets both columns through the same MCP and adds them, which is the failure described in three MCPs, three revenues.
A synthetic example with round numbers: a Shopify store booked $1M in net sales in September. GA4 recorded $1.1M in purchase revenue, because orders cancelled or refunded after checkout stayed counted there (why Shopify and GA4 disagree). Amazon sold another $200k that no ad platform sees. Ask Claude, through a connector, “what was September revenue?” and it answers from whichever source is closest to hand. The arithmetic will be right and the number wrong.
This is metric hallucination, a model computing correctly on a definition nobody wrote down. In a paired benchmark from April 2026, giving the model the business definitions raised answer accuracy from 45.5–50.5% to 67.7–68.7% (Rumiantsau and Fokeev, 2026). A connector doesn’t make that number worse. It just can’t make it better, because it carries no definitions.
Funnel and Improvado recognize the problem and give you a place to put the rule. The question left is who writes it, who signs off, and who updates it when finance changes what counts as a sale. If the answer is “a media buyer, when there’s time,” the place exists and stays empty. What a useful definition actually contains is laid out in what goes into a semantic layer.
Three of the four MCP servers in the table can also change campaigns. With write access on undefined data, an agent that reads wrong also acts wrong: it pauses the campaign that, by your books, was selling. Before you turn it on, read what a platform MCP server can and can’t see.
When should you not choose Precisian?
A small team that only wants the weekly report in Sheets or Looker Studio. If the question is “how much did we spend and how many clicks did each campaign get,” and the reader is a person who knows the platforms, a connector is the right tool. Windsor.ai Basic is $19 a month billed annually and Supermetrics Starter is $39 (Windsor.ai; Supermetrics). No managed platform competes with that, and none should try.
A single-source business. A store that sells only on its own site and advertises only on Google has nothing to reconcile. Native reporting is enough.
A data team that already has a warehouse and written definitions. What’s missing is ingestion, and Funnel or Improvado will give your team more direct control. The cost logic on both sides is in build vs. buy a data lake.
Anyone looking for a ready-made dashboard. Precisian doesn’t sell dashboards. Delivery ends at the semantic layer, and consumption happens in the client’s own AI, BI or automation.
What should each profile choose?
Weekly report, one person reading it: Windsor.ai or Supermetrics on the entry plan. Choose by the destination you already use.
A media team that wants to ask Claude about media, and only media: a connector with MCP works. Start read-only (Funnel ships that way) and grant write access only once you know what the agent does with it.
An agent answering leadership about revenue, with Shopify, Amazon and an ERP in the mix: you need written definitions before you need another connector. With a data team to write and maintain the rules, Funnel or Improvado give you the place. Without that team, the choice is a managed platform where semantic modeling is done with your team as part of the contract.
A multi-brand group or an agency in the middle: isolation dominates. Ask each vendor, in writing, how one brand’s data is kept apart from another’s.
What does this article not cover?
It doesn’t compare connector quality source by source; that depends on your accounts and changes with every API version. It gives no Enterprise pricing for any of the four, because none publishes it. I didn’t test MCP latency or rate limits. And Windsor.ai’s prices are rendered by JavaScript on its pricing page; I checked them on the rendered page and in the same page’s FAQ on October 14, 2026, but they change without notice, so verify before you sign.
If your agent already returns a revenue figure that doesn’t match your books, the first step is measuring the gap between the two and finding out which definition each one used. What a managed data platform includes to close that gap, and where pricing starts, is on Precisian’s pricing page, with no contract commitment to look.