List models

Lists the inference models deployed in the caller's org.

GET /v1/ml/models

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Address	`https://api.hanzo.ai/v1/ml/models`
Method	`GET`
Operation	`get_ml_models`
Auth	`Authorization: Bearer $HANZO_API_KEY`

Lists the inference models deployed in the caller's org. Each entry carries the model's name, when Kubernetes admitted it, and kserve's live status — the spec is on the single-model read. An org that has deployed nothing gets an empty list.

Request

GET /v1/ml/models takes no parameters and no body — the credential is the whole request.

Response

Status	Body	Meaning
`200`	ml.mlResourceList	ok
`default`	problem-details	refused

200 body — 7 fields.

Field	In	Type	Always	Description
`items`	body	ml.mlResource[]	—	Items is one entry per object, newest LAST (the Kubernetes list order).
`items[].createdAt`	body	string	—	CreatedAt is when Kubernetes admitted the object, RFC 3339 in UTC.
`items[].name`	body	string	—	Name is the object's metadata.name, unique within the caller's namespace.
`items[].spec`	body	object	—	Spec is the resource spec, verbatim as Kubernetes stores it.
`items[].spec.*`	body	any	—
`items[].status`	body	object	—	Status is the live status kserve owns, verbatim.
`items[].status.*`	body	any	—

Failure carries the platform error shape — see Errors.

Examples

CLI

SDK

HTTP

MCP

hanzo ml models list

.ts

.py

.go

.rs

.java

import { Configuration, MlApi } from 'hanzoai';

const api = new MlApi(new Configuration({ accessToken: process.env.HANZO_API_KEY }));
const { data } = await api.getMlModels();

from hanzoai.cloud import ApiClient, Configuration
from hanzoai.cloud.api import MlApi

client = ApiClient(Configuration(access_token=os.environ["HANZO_API_KEY"]))
result = MlApi(client).get_ml_models()

cfg := hanzoai.NewConfiguration()
cfg.AddDefaultHeader("Authorization", "Bearer "+os.Getenv("HANZO_API_KEY"))
client := hanzoai.NewAPIClient(cfg)

resp, _, err := client.MlAPI.GetMlModels(context.Background()).Execute()
if err != nil {
	return err
}

use hanzo_client::apis::{configuration::Configuration, ml_api};

let mut cfg = Configuration::new();
cfg.bearer_access_token = std::env::var("HANZO_API_KEY").ok();

let result = ml_api::get_ml_models(&cfg, Default::default()).await?;

import ai.hanzo.cloud.ApiClient;
import ai.hanzo.cloud.api.MlApi;

ApiClient client = new ApiClient();
client.setBearerToken(System.getenv("HANZO_API_KEY"));

var result = new MlApi(client).getMlModels();

curl https://api.hanzo.ai/v1/ml/models \
  -H "Authorization: Bearer $HANZO_API_KEY"

MCP reaches ml through the ml tool, which names its 4 operations with its own verbs — this one among them, under a name only MCP declares. describe explains any of them:

curl -X POST https://api.hanzo.ai/v1/mcp \
  -H "Content-Type: application/json" \
  -d '{
       "jsonrpc": "2.0",
       "id": 1,
       "method": "tools/call",
       "params": {
         "name": "describe",
         "arguments": {
           "op": "list_ml_models"
         }
       }
     }'

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