The API copilot that runs on your machine.
AI that generates requests, explains failures, and writes tests — running on local, on-device models, so your API data never leaves your PC.
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The workspace it's built on is already here — try Karve today →
API work is repetitive, fragmented, and often sensitive — yet the tools that speed it up want your endpoints and tokens in the cloud. Karve AI does the grunt work on your machine instead.
What Karve AI will do
Generate requests from a sentence — or a cURL.
Describe it in plain English, paste a cURL, or point at your docs — Karve AI writes a clean, runnable .http request you can send on the spot.
# @name createOrder POST {{baseUrl}}/orders Authorization: Bearer {{token}} Content-Type: application/json { "sku": "K-2049", "quantity": 2 }
Explain failed calls
Karve AI reads the status, headers, variables, request body, and response, then tells you what went wrong and how to fix it.
401 → "Your token variable is empty."
Suggest tests & assertions
From a real response, Karve AI proposes assertions worth keeping — status, shape, and the fields that actually matter.
expect status 200 · body.id is present
Extract variables & auth
Spot the host, tokens, and IDs repeated across requests and lift them into reusable variables and a clean auth pattern.
@baseUrl · {{token}} · @apiVersion
Generate docs & onboarding
Turn a working set of requests into readable API notes a teammate can follow on day one — straight from your real workflow.
requests → onboarding notes
Where it fits your day
Debug a failing call in place
A 4xx you can't explain? Ask why — Karve AI points at the header, variable, or body that's off, without you leaving the workspace.
Onboard to an unfamiliar API
Inherit a folder of requests with no context? Ask Karve AI what they do and how they fit together, and get oriented fast.
Keep internal APIs internal
Working with private endpoints, tokens, or unreleased APIs? The AI runs locally, so none of that context is uploaded anywhere.
Your API context is sensitive. It should stay yours.
Internal endpoints, tokens, private schemas, unreleased APIs — the things you debug daily are exactly what you can't paste into a cloud AI tool. Karve AI runs the model on your machine, built for the Windows AI PC era where NPUs and GPUs make on-device inference practical. AI help, without the upload.
Built for
The plan
Stage 1 — Local API workspace
The native Windows app that's already live: organize, run, and inspect .http requests locally.
Stage 2 — AI-assisted workflow
Generate requests, explain failures, suggest tests, and document APIs — the capabilities on this page, brought into the workspace.
Stage 3 — On-device copilot
A copilot tuned for Windows AI PCs and NVIDIA RTX / DGX Spark — local models doing the repetitive API work while your data stays put.
Already using Claude Code? Karve MCP comes first.
The next version ships a built-in MCP server, so your existing AI agent can find, run, and fix .http requests — without ever seeing your tokens or environments.
Common questions
Is Karve AI really local / on-device?
That's the whole design. Karve AI is built to run models on your machine, so your endpoints, tokens, and schemas never leave the PC.
Will it cost extra or need a subscription?
Karve AI is still in development. We'll share availability and any pricing closer to launch — today's Karve is a one-time purchase with no subscription.
What hardware will it need?
It's being built for Windows AI PCs with NPU/GPU acceleration — including NVIDIA RTX and DGX Spark. Exact requirements will be confirmed at launch.
When will it be available?
No date yet. Get notified and we'll reach out when it's ready.
Karve AI is coming. The workspace it's built on is here today.
The AI features are in the works. The native, local-first Karve they're built on is already on the Microsoft Store — start there.
Want a ping when Karve AI ships?
Karve AI updates only — no spam, unsubscribe anytime.