Xiaomi MiMo Reasoning Model (github.com)

I know AI is peak hype right now. But it has definitely changed some of our dev workflows already. So we wanted to find a way to let our customers experiment with how they can use AI to make their cloud cost management work more productive.

The MCP Server acts as a connector between LLMs (right now only Claude, Cursor support it but ChatGPT and Google Gemini coming soon) and your cost and usage data on Vantage which supports 20+ cloud infra providers including AWS, Datadog, Mongo, etc. (You have to have a Vantage account to use it since it's using the Vantage API)

Video demo: https://www.youtube.com/watch?v=n0VP2NlUvRU

Repo: https://github.com/vantage-sh/vantage-mcp-server

It's really impressive how capable the latest-gen models are with an MCP server and an API. So far we have found it useful for:

Ad-Hoc questions: "What's our non-prod cloud spend per engineer if we have 25 engineers"

Action plans: "Find unallocated spend and look for clues how it should be tagged"

Multi-tool workflows: "Find recent cost spikes that look like they could have come from eng changes and look for GitHub PR's merged around the same time" (using it in combination with the GitHub MCP)

Thought I'd share, let me know if you have questions.

Comments (16)

_pdp_ · 5h ago

On a related note, I'm not sure when it became "ok" to leave production credentials scattered across your system in configuration files. So many MCP server examples encourage this pattern, and inevitably, it's going to cause trouble at some point.

Game_Ender · 1h ago

What is your preferred way to manage them?

devenjarvis · 54m ago

The 1pass CLI is great! However if you aren’t using 1password as your secrets vault, I’m building an open source, vault-agnostic alternative called RunSecret (https://github.com/runsecret/rsec)

ivanvanderbyl · 1h ago

1Password’s CLI op does a reasonably good job of this

ponywombat · 7h ago

AWS have also made their own cost analysis MCP server https://github.com/awslabs/mcp/tree/main/src/cost-analysis-m...

neuroelectron · 4h ago

What a great solution. They can leverage this to avoid liability for their own price quotes and solutions while simultaneously adding another layer of vender lock-in. synergy

cowsandmilk · 2h ago

How does this avoid liability for anything?

mcintyre1994 · 2h ago

I don't think anyone's really stated this outright, but large companies must believe they're not liable for anything their models/AI products are producing. That must be the case for their business model to work.

neuroelectron · 1h ago

A better question is how can they be held liable at all.

mdaniel · 11h ago

How does this work? https://github.com/vantage-sh/vantage-mcp-server?tab=License...

That is extra weird when thinking about the audience who might be Vantage.sh users (and thus have the ability to create the read-only token mentioned elsewhere) but would almost certainly be using it from their workstation, in a commercial context. Sounds like you're trying to keep someone from selling your MCP toy and decided to be cute with the licensing text

bluck · 9h ago

I'm just trying to understand licenses, but doesn't the choice of MIT contradict the inital "non-commercial purposes" as MIT says 'including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software' - Therefore, the non-commercial purposes is actually void and I can use the software to the limits of MIT defines? And because it is already MIT, they can relicense only future software but not this piece anymore?

skwashd · 7h ago

IANAL but that is my understanding. I created an issue to get some clarification - https://github.com/vantage-sh/vantage-mcp-server/issues/31

globalise83 · 54m ago

So if I want to use the software I just have to create a fork on my home machine for non-commercial purposes, update the license to MIT only, and then the fork is mine to do with as I want commercially? What's even the point of this license?

andrenotgiant · 4d ago

What's the difference between connecting an LLM to the data through Vantage vs directly to the AWS cost and usage API's?

StratusBen · 4d ago

A few things.

The biggest is giving the LLM context. On Vantage we have a primitive called a "Cost Report" that you can think of as being a set of filters. So you can create a cost report for a particular environment (production vs staging) or by service (front-end service vs back-end service). When you ask questions to the LLM, it will take the context into account versus just looking at all of the raw usage in your account.

Most of our customers will create these filters, define reports, and organize them into folders and the LLM takes that context into account which can be helpful for asking questions.

Lastly, we support more providers beyond AWS so if you wanted to merge in other associated costs like Datadog, Temporal, Clickhouse, etc.

cat-whisperer · 4d ago

This is going to different, as resources end up getting intertwined? or is there a way to standardize it?