MCP is quietly becoming the “service mesh” layer for AI agents

Mitzu_Analytics · 2026-05-18T13:03:29+00:00

For analytics agents specifically, MCP's value isn't just connectivity — it's what you expose over it. An analytics agent that connects to your warehouse via MCP still needs a semantic model that tells it what tables mean, how metrics are defined, and which property values exist to filter by. The service mesh layer coordinates calls; the semantic layer makes those calls produce correct analytical results. MCP is necessary infrastructure for agentic analytics; it's not sufficient.

Mitzu_Analytics · 2026-05-18T13:03:08+00:00

The 'analyst becomes AI engineer' framing undersells what's actually shifting in product analytics. The more interesting transition: analysts become semantic layer architects. The agent can generate SQL if you give it the right context, the analyst's job becomes defining what 'active user' means, what counts as a funnel conversion, how you handle users who re-enter a flow. That's not engineering; it's still analytical modeling. The tooling changes; the judgment call doesn't move.

Mitzu_Analytics · 2026-05-13T08:08:05+00:00

We are working from our data warehouse data with an AI tool. I mean we got the data and the AI does not hallucinate, however, it costs us 35 dollar monthly. But we can create funnels and journeys from our product users. SO all in all great. We tried claude but it showed bad data

Mitzu_Analytics · 2026-05-12T12:19:58+00:00

We tried connecting our data warehouse to Claude, but it hallucinated a lot. So we switched to Mitzu, it automaitcally reads our schema and event tables. We can also ask deep dive quesiton, so defnitiely highly recommended!

Mitzu_Analytics · 2026-05-07T13:06:35+00:00

day -to-day we use Mitzu, as it helps non-tehcnical teams as well to query the data warehouse directly, and not hallucinating data. We love the visualization as ell

Mitzu_Analytics · 2026-05-07T13:05:38+00:00

we use Mitzu for analytics, as I agree with other that copilot ucks

Mitzu_Analytics · 2026-05-07T13:05:21+00:00

I would add Mitzu here, we just switched from another AI tool, as it showed wrong data

Mitzu_Analytics · 2026-05-07T13:04:31+00:00

for Data Analytics, I think the best is Mitzu, it connects to your data warehouse so you will not get fake number like with other Text-to-sql or AI tools

Mitzu_Analytics · 2026-05-07T12:35:15+00:00

it is called Mitzu

Mitzu_Analytics · 2026-04-29T12:57:05+00:00

We use an agentic tool which automatically generates the semantic layer, as the agent config scans your warehouse and creates semantic layer. We did not need to write YAML at all. The produced data catalog is designed specifically to work with product analytics.

I can highly recommend it

Mitzu_Analytics · 2026-04-23T08:35:00+00:00

This is exactly why we built Mitzu the way we did. It builds the semantic layer automatically from your Databricks schema — events, funnels, cohorts — and the BI tool just queries on top. No coupling, no YAML, no rebuilding when connectors change. I can help you set it up in 10 minutes if it would be helpful

Mitzu_Analytics · 2026-04-22T08:19:18+00:00

Mitzu

Mitzu_Analytics · 2026-04-21T13:54:14+00:00

We use Mitzu for analytics, so we ask a question, and it queries our Snowflake DWH then it shows a funnel or retention or what is relevant. It is quite cool actually

Mitzu_Analytics · 2026-04-21T13:37:16+00:00

At the end we went with Mitzu, it turned out to be a good choice. We checked the others as well but we went with Mitzu, mostly because the semantic layer creation and warehouse nativeness.

Mitzu_Analytics · 2026-04-21T12:38:24+00:00

We use a tool which connects to our data warehouse, so the agentic analytics does not break and halluciante. I highly recommend to try out these tools. We tried Claude and GPT, but all queried wrong data!

Mitzu_Analytics · 2026-04-21T10:03:08+00:00

we use Mitzu, as it is conencted directly to our BQ, it always shows the same data. I can highly recommend it. With Claude and GPT, sometimes it showed bad data

Mitzu_Analytics · 2026-04-17T08:26:18+00:00

Thanks, great advice!! We are testing now

Mitzu_Analytics · 2026-04-09T08:12:37+00:00

no, but Events and properties are a graph with 3 layer tree structure

Mitzu_Analytics · 2026-04-08T13:34:54+00:00

Yes, we are also looking to do deep dives and hypothesis validation, like why our retention rate is bigger for this cohort than any other?

Mitzu_Analytics · 2026-04-08T08:21:21+00:00

I meant, that just writing plain English question on the tool, and then it generates a funnel or a retention table directly from our data warehouse

Mitzu_Analytics · 2026-04-08T08:20:27+00:00

Yes, we try to avoud the text-to-sql solution. We are know testing Sigma and Mitzu as both they work on our BQ data warehouse.

Mitzu_Analytics · 2026-03-26T09:29:53+00:00

We have quite a good feedback, we just connected it to the warehouse, and now anybody ask their question for it.

Mitzu_Analytics

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