# Kubeflow MCP Server

> Use this tool when you need to streamline Kubeflow training job management through natural language interactions, solving the problem of complex job submissions and monitoring for AI agents. It takes natural language inputs and outputs job status and results, allowing for effortless management of Kubeflow workflows. This tool is ideal for use cases where AI agents require automated job planning, submission, and monitoring without requiring Kubernetes or Kubeflow SDK expertise.

Canonical page: https://skillsregistry.net/skills/kubeflow-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/kubeflow-mcp-server

## Description

Enables AI agents to plan, submit, monitor, and manage Kubeflow training jobs through natural language, without needing to learn Kubernetes or the Kubeflow SDK.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/gf23zz1dp3)
- **Repository:** <https://github.com/kubeflow/mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "kubeflow-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kubeflow-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kubeflow-mcp-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt