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Connect Anyscale to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Manage foundational models and cluster jobs via chat.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 7 capabilities

We ship only the actions that matter.

Capability set01 / 02

01-04

4 capabilities in this set.

Part of 7 available through Anyscale.

  1. 01

    Text completion

    Use for foundational instruct generation. Generate text completion using Anyscale generic completion API

  2. 02

    List models

    G., meta-llama/Llama-2-70b-chat-hf). List available AI models on Anyscale Endpoints

  3. 03

    Chat completion

    Pass an array of messages with roles (user, assistant, system). Generate conversational responses via Anyscale LLMs

  4. 04

    Generate embeddings

    Generate semantic vector embeddings for text

Capability set02 / 02

05-07

3 capabilities in this set.

Part of 7 available through Anyscale.

  1. 05

    List services

    List Anyscale deployed services

  2. 06

    Get service

    Retrieve details about a specific Anyscale service

  3. 07

    List jobs

    List Anyscale batch or training jobs

Real work

What teams actually run

01

Debugging a Service Endpoint

A backend developer needs to know why a specific service is failing. They ask the agent to retrieve the service details, getting the status and endpoint configuration instantly.

02

Pre-processing Data for RAG

A data scientist needs to index a large document set. They use the MCP to generate vector embeddings for the text, preparing the data for a retrieval-augmented generation system.

03

Checking Training Run Status

An MLOps engineer needs to know if a nightly model retraining job finished successfully. They query the MCP to list jobs and check the final execution status.

04

Quick Model Testing

A data scientist wants to test a new prompt against a foundational model. They use the chat completion capability to run zero-shot prompts and compare results.

Automate a task

Put Anyscale to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Anyscale works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Anyscale to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

907ms average. Fast in production.

Anyscale is checked daily against the live service.

Daily averagePeak 1009ms
Oct 12Today
Fastest day
662ms
Slowest day
1009ms
14-day trend
Slowing+34%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 7 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Anyscale, so you can see the experience inside your AI.

It does not authenticate your account with Anyscale. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Anyscale Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_TYJFZRqD4R2R9l7bu7Vxd494Pf6ounExJTsky8LF/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Anyscale capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "anyscale-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_TYJFZRqD4R2R9l7bu7Vxd494Pf6ounExJTsky8LF/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Anyscale in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Anyscale owners hand off.

This MCP is built for technical teams managing complex AI pipelines. If your job involves inspecting deployed models, debugging service health, or monitoring background compute jobs, this connector handles the heavy lifting so you don't have to open a terminal.

  • 01

    AI & MLOps Engineers

    Automate the inspection of deployed models, jobs, and embeddings safely during CI workflows.

  • 02

    Data Scientists

    Submit rapid completion tasks to specialized LLMs running inside your Anyscale VPC.

  • 03

    Backend Developers

    Debug service health metrics and endpoint statuses without navigating the heavy cloud dashboard.

FAQ

Questions Anyscale owners ask.

  • 01

    Do I need to use the command line to manage my Anyscale cluster?

    No. This MCP lets you manage your entire infrastructure conversationally. You can check Ray cluster status, list services, and query job metrics directly through your AI agent.

  • 02

    What kind of models can I access?

    You can list all active foundational models available in your environment. The MCP supports both simple text completion and complex conversational responses using chat completion.

  • 03

    Is this good for MLOps workflows?

    Yes. It is designed for MLOps engineers who need to automate the inspection of deployed models, jobs, and embeddings during CI workflows. You get visibility without leaving your chat interface.

  • 04

    How does the embedding process work?

    You use the generate embeddings capability to pass text arrays. The MCP then generates semantic vector embeddings, which are necessary for advanced data retrieval systems.

  • 05

    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.

  • 06

    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.

  • 07

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

    Yes. This MCP 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.

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