u/getnable

been building nable, an MCP server for cloud + AI cost. you point your editor at it and ask stuff like "why did the bill spike" against your own AWS/GCP/Azure and LLM providers. the two pieces i think this sub will actually care about are the agent guardrail and the normalization, so let me talk about those.

the agent part. agents in cursor/claude code increasingly run real infra commands, terraform apply, kubectl, gcloud. that's great until one spins up a GPU fleet that shows up as a surprise line item next month. nable can sit in front of that: before an action runs, it estimates what the change costs and checks it against your budget/policy, and returns allow / needs-review. it's propose-only by design, it never executes anything itself. so the flow is your agent proposes → nable prices it and flags it → you decide. it also knows a t3.micro from a p4d.24xlarge, so "this is safe" and "this is a $12k/mo mistake" come back as different answers.

the normalization part. every provider bills in a completely different shape. AWS gives you flat CUR columns, Azure Cost Management is its own thing, GCP is BigQuery export rows with a nested credits[] array, Datadog is a charges array, and the LLM providers are per-model token dicts. nable maps all of them into one schema (FOCUS 1.2) so a question like "compute vs database vs AI spend across everything" actually resolves. the part i found surprisingly fiddly: commitment discounts. AWS Savings Plans, Azure reservations, and GCP committed-use discounts are each represented totally differently, and getting them all to land in the same "effective cost" field so cross-provider totals aren't lying took real work. once it's normalized, the cross-view is the payoff, my own bill turned out ~70% Textract + Bedrock, not the EC2 I'd assumed.

it's local-first (runs on your machine, read-only into your providers, credentials never leave). free for solo, every connector included. uvx nable in a terminal, or point claude desktop / cursor / claude code at it.

would love feedback from folks building servers, especially on the pre-action guardrail pattern, curious if anyone else is doing cost/policy checks before an agent acts, or if there's a cleaner convention than a dedicated "check this action" tool.

MCP server for cloud + AI cost. point your editor at it, ask "why did the bill spike" against your own AWS/GCP/Azure + LLM providers. two parts worth calling out:

agent guardrail. before your agent runs terraform/kubectl, nable estimates what the change costs and checks it against budget/policy → allow or needs-review. propose-only, never executes anything itself. so "this is safe" and "this is a $12k/mo mistake" come back as different answers.

normalization. every provider bills in a different shape (AWS CUR columns, GCP BigQuery rows, LLM token dicts...). nable maps them all to one schema so "compute vs AI spend across everything" actually resolves. even the commitment discounts (savings plans, reservations, GCP CUDs) land in the same field. the payoff is the cross-view, my own bill was ~70% Textract + Bedrock, not the EC2 I assumed.

local-first, read-only, credentials never leave your machine. free for solo. uvx nable or point claude desktop / cursor at it.

curious if anyone's doing cost/policy checks before an agent acts, or if there's a cleaner pattern than a dedicated "check this action" tool.