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Vinkius

Anyscale Connector for AI agents.

7 live capabilities

Manage your Ray cluster and LLM inference infrastructure from your AI client.

Live agent request Anyscale / Connector

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AI Agent

Why people use Anyscale

Anyscale for MLOps Infrastructure Management

With this Connector, you can stay in your workspace and ask your agent to do the heavy lifting. You just ask for a status update or a list of active models, and the agent pulls that data for you. You get a clear picture of your infrastructure without the constant tab-switching.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

You get a conversational interface for your entire Anyscale and Ray infrastructure.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

  1. Real-world use case 01

    Checking if a training job failed

    A data scientist needs to see if their latest run crashed.

  2. Real-world use case 02

    Verifying available models

    An engineer needs to know which LLMs are ready for production.

  3. Real-world use case 03

    Debugging a failing endpoint

    A developer notices a service is acting up.

Complete set · 7capabilities

The complete Anyscale capability set.

These are the exact actions your AI can choose when you ask it to work with Anyscale.

Capability set01 / 02

01—04

4 capabilities in this set.

Part of 7 available through Anyscale.

  1. 01 Capability

    List models

    See all foundational models currently active in your Anyscale environment. This helps you identify which models are ready for inference.

  2. 02 Capability

    Chat completion

    Send conversational messages to your hosted LLMs and get responses back. It makes it easy to interact with your private models through your agent.

  3. 03 Capability

    Text completion

    Generate text completions using your generic Anyscale completion API. This is useful for foundational instruct generation tasks.

  4. 04 Capability

    Generate embeddings

    Create semantic vector embeddings for text inputs directly through your agent. You can use this to build out your data pipeline in real time.

Capability set02 / 02

05—07

3 capabilities in this set.

Part of 7 available through Anyscale.

  1. 05 Capability

    List services

    Get a full list of all services currently deployed on your Anyscale platform. It gives you a high level view of your deployed fleet.

  2. 06 Capability

    Get service

    Pull specific details and configuration data for a single Anyscale service. Use this to debug specific endpoint statuses or health metrics.

  3. 07 Capability

    List jobs

    View all batch and training jobs to check their recent execution status. This allows you to monitor training progress without leaving your workspace.

Set up in minutes

One URL. Then ask Anyscale to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Anyscale from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_TYJFZRqD4R2R9l7bu7Vxd494Pf6ounExJTsky8LF/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it Anyscale, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Anyscale for the conversation.

Where the request belongs

Work Anyscale can move forward.

Built around the request

This is for MLOps engineers and data scientists who are tired of manually checking cluster logs and dashboard metrics at all hours of the day.

01

MLOps Engineer

Debugging service health and monitoring Ray cluster statuses during production deployments.

02

Data Scientist

Quickly submitting completion tasks to specialized LLMs inside a private VPC.

03

Backend Developer

Checking live service endpoint configurations without navigating the cloud console.

Build the capability set

Add more capabilities.

Each Connector adds new actions and data without changing how you work.

Browse Connectors
DeepInfra (Serverless LLM Inference) logo
01 4 capabilities

DeepInfra (Serverless LLM Inference)

Run top-tier LLMs, image generation, and embeddings via DeepInfra's serverless infrastructure directly from your AI agent.

View Connector
Eden AI logo
02 13 capabilities

Eden AI

Access 100+ AI models through a single API. route LLMs, generate embeddings, and execute specialized AI tasks like OCR and translation.

View Connector
Together AI logo
03 7 capabilities

Together AI

Generate code, evaluate embeddings, and deploy open-source LLMs instantly from your local agent via Together AI's infrastructure.

View Connector
Mistral AI (Frontier LLMs & Embeddings) logo
04 7 capabilities

Mistral AI (Frontier LLMs & Embeddings)

Manage AI inference via Mistral. execute chat completions, generate RAG embeddings, and audit frontier models.

View Connector
AirOps logo
05 10 capabilities

AirOps

AI workflow orchestration. execute models, manage agents, and query memory via AI.

View Connector
Predibase (LLM Serving & Finetuning) logo
06 7 capabilities

Predibase (LLM Serving & Finetuning)

Deploy and query fine-tuned LLMs via Predibase. run inference, classify text, and monitor deployment metrics directly from your AI agent.

View Connector

Bring your own AI

Change the model, client or framework. Keep Anyscale connected.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • VS Code
  • Windsurf
  • ZCode
  • Cline
  • Zed
  • Continue
  • Kiro
  • Roo Code
  • Zencoder
  • Goose
  • Void
  • Augment Code
  • Amp
  • Qodo
  • Tabnine
  • Pieces
  • Sourcegraph Cody
  • JetBrains
  • Warp
  • Amazon Q
  • Antigravity
  • BoltAI
  • Raycast
  • Jan
  • LM Studio
  • AnythingLLM
  • Open WebUI
  • Msty
  • Cherry Studio
  • LibreChat
  • TypingMind
  • Chorus
  • 5ire
  • n8n
  • LangChain
  • LlamaIndex
  • CrewAI
  • Vercel AI SDK

Before you connect

Questions about Anyscale.

The practical details behind the request, access and result.

Can I use Anyscale MCP to manage my Ray clusters?

Yes, you can monitor your Ray services and check cluster job statuses directly through your AI agent. It gives you a real-time look at your distributed computing environment without needing to log into a separate dashboard.

Does Anyscale MCP support generating embeddings?

Yes, you can generate semantic vector embeddings for text inputs on the fly. This makes it easy to integrate embedding generation into your data pipelines using just natural language.

How do I see my active models with Anyscale MCP?

You can simply ask your agent to list the models currently active in your environment. It will pull the list of foundational models that are ready for inference for you.

Can I debug my services with Anyscale MCP?

Yes, you can pull specific details and configuration data for any service in your fleet. This helps you quickly check endpoint statuses and health metrics during production.

Is Anyscale MCP good for MLOps engineers?

It's built for MLOps workflows. It automates the inspection of deployed models and batch jobs, making it much easier to monitor your infrastructure during CI/CD cycles.

Can I run inference tasks using Anyscale MCP?

Yes, you can send prompts to your hosted LLMs to generate conversational or text completions. It connects your agent to your private models for secure inference.

Does Anyscale MCP work with Cursor or Claude?

Yes, it works with any MCP-compatible client. Once you connect it, you can manage your Anyscale and Ray infrastructure from your favorite AI workspace.

Can I query a Llama 3 model that is locally deployed in Anyscale?

Yes. First ask the agent to list the available model APIs using list_models so it can grab the precise namespace (e.g. meta-llama/Llama-3-70b-instruct). Then, ask it to run chat_completion pointing at that specific ID. You are now effectively chaining your local agent with an enterprise-sized foundational model in your own VPC.

Is it possible to check whether my training job timed out without opening the Anyscale Dashboard?

Absolutely. Use the list_jobs capability directly from your chat workflow. It will pull down the state of recent tasks (running, failed, succeeded) alongside metrics. The agent can immediately summarize issues if it sees any errors, saving you a context switch.

Can I use Anyscale to process my text chunks into Vectors inside a project pipeline?

Yes. This Connector comes with an explicit generate_embeddings capability mapped to your Anyscale endpoints. By providing arrays of chunks, the Anyscale fast backbone will return your high-dimensional vectors. Your custom Agent can wrap this into scripts to hydrate vector databases faster.

One connection away

Give your agent a direct line to Anyscale.

Connect Anyscale once. Keep it beside 5,900+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available