Vinkius

Anyscale MCP for AI Agents. Manage MLOps Cluster Jobs and Model Inference

The Anyscale MCP lets your AI client manage entire distributed machine learning environments through natural conversation. You can list models, generate vector embeddings for large text arrays, monitor deployed services, and check complex Ray cluster job statuses—all without opening a terminal or navigating a heavy cloud dashboard.

Anyscale MCP for AI Agents MCP is compatible with Claude Claude
Anyscale MCP for AI Agents MCP is compatible with ChatGPT ChatGPT
Anyscale MCP for AI Agents MCP is compatible with Cursor Cursor
Anyscale MCP for AI Agents MCP is compatible with Gemini Gemini
Anyscale MCP for AI Agents MCP is compatible with Windsurf Windsurf
Anyscale MCP for AI Agents MCP is compatible with VS Code VS Code
Anyscale MCP for AI Agents MCP is compatible with JetBrains JetBrains
Anyscale MCP for AI Agents MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

list_models

Lists all foundational AI models available on your Anyscale Endpoints cluster.

chat_completion

Generates conversational replies by sending structured messages with roles (user, system, assistant) to Anyscale LLMs.

text_completion

Creates text completions using the general Anyscale API when you need foundational, non-conversational text generation.

generate_embeddings

Processes arrays of text and generates semantic vector embeddings that can be used for advanced search or RAG systems.

list_services

Retrieves an overview list of all currently deployed services on your Anyscale platform.

get_service

Fetches specific, detailed information about a single designated Anyscale service deployment.

Lists all running or completed batch and training jobs managed by your Ray cluster on Anyscale.

Waiting for input…

AI Agent
Anyscale MCP for AI Agents

What AI agents can do with Anyscale MCP: 7 Tools for Vector Embeddings & Cluster Management

These tools let you manage everything from listing foundational AI models to running complex batch jobs and generating vector embeddings, all within a conversational flow.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Anyscale MCP

List Models

Lists all foundational AI models available on your Anyscale Endpoints cluster.

Chat Completion

Generates conversational replies by sending structured messages with roles (user...

Text Completion

Creates text completions using the general Anyscale API when you need foundational...

Generate Embeddings

Takes a piece of text and creates its corresponding semantic vector embedding array.

List Services

Retrieves an overview list of all currently deployed services on your Anyscale...

Get Service

Fetches specific, detailed information about a single designated Anyscale service deployment.

List Jobs

Lists all running or completed batch and training jobs managed by your Ray cluster on Anyscale.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Anyscale MCP for AI Agents MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Anyscale MCP for AI Agents integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Anyscale, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
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Anyscale MCP for AI Agents: Managing MLOps Cluster Jobs

Today, checking the status of a batch job or validating model deployment involves jumping between three different places: the Ray cluster dashboard, the service registry UI, and the logs viewer. You copy statuses from one place into a spreadsheet just to track failures.

With this MCP, you simply tell your agent what you need to know about the cluster jobs. It queries the necessary services behind the scenes, pulling the execution status and training metrics directly into the chat interface. The result is an immediate answer, not a link to three different dashboards.

Anyscale MCP for AI Agents: Controlling Model Inference Workflows

Running complex LLM queries means juggling model names, API keys, and whether the required models (like Llama-2) are actually deployed. You spend time verifying if the foundational model is available before you can even start writing your prompt.

This MCP gives you instant visibility via `list_models`. It shows every single active model ready to receive inference traffic, confirming deployment status in one quick conversation. That immediate confirmation keeps your workflow moving without delay.

What Anyscale MCP for AI Agents MCP does for your AI

This connector connects your AI agent directly to the Anyscale environment, letting you manage both large-scale LLM queries and underlying backend infrastructure natively. Instead of logging into a clunky web portal just to check if a training job finished, you talk to your agent. It handles the complex background work for you.

It provides tools to list active foundational models and run chat completions using specialized Anyscale LLMs. You can also generate semantic vector embeddings from text inputs on the fly. Furthermore, it lets you monitor deployed Ray services and query batch jobs to inspect their recent execution statuses and training metrics via conversation.

If you're already using Vinkius for your other APIs, adding this MCP gives you a single point of control over your entire MLOps stack.

Built · Hosted · Managed by Vinkius Anyscale MCP for AI Agents — MLOps Cluster Management
Server ID 019d754e-a2ee-73d3-8d87-cd2019c58c1a
Vinkius Inspector
Compliance Grade F
Score 43.65/100
Vinkius Inspector Badge — Score 43.65/100

Frequently asked questions about Anyscale MCP for AI Agents MCP

How does the Anyscale MCP help me check my cluster job status? +

The Anyscale MCP lets you query your Ray batch jobs directly through conversation. Instead of opening a complex terminal dashboard, simply ask about recent job statuses to see if training succeeded or failed and why.

I need to find out which LLMs are available on my cluster using the Anyscale MCP? +

You can use the MCP to list all active foundational models. It gives you a clean rundown of every deployed model, confirming its name and current status before you write a single line of code.

What if my service endpoint is having issues? Can Anyscale MCP help me debug it? +

Yes, the MCP allows you to retrieve specific details about your deployed services. This means you can confirm the latest endpoint configurations and check the current health status of a microservice in plain language.

Does Anyscale MCP handle generating embeddings for my documents? +

It does. You pass text to the MCP, and it generates semantic vector embeddings using your configured model. This makes preparing data for search or RAG pipelines much easier than running separate scripts.

How do I connect Anyscale MCP to my AI agent? +

You subscribe to this MCP in the Vinkius catalog, providing your necessary Anyscale API keys. Your agent then handles all the communication with the cluster tools for you.