Vinkius

Baseten MCP for AI Agents. Orchestrate machine learning model deployments and predictions

Baseten connects your AI agents directly to your machine learning infrastructure. Your agent can now manage entire model lifecycles—from listing deployed models to running real-time predictions on GPU weights and auditing sensitive workspace secrets.

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

Give Claude and any AI agent real-world access

List all deployed models

See a comprehensive list of every ML model currently managed within your Baseten account.

Retrieve specific model details

Get full configuration information for any individual model ID you specify.

Run serverless predictions

Execute real-time, low-latency inference by feeding tensor shapes or JSON directly into a deployed model instance.

Audit active deployment states

List and inspect the current replica counts and autoscaling configurations for specific models.

Check workspace secrets

Enumerate all active environment variables and secrets stored securely within your isolated ML orchestration space.

Waiting for input…

AI Agent
Baseten MCP for AI Agents

What AI agents can do with 6 Tools in the Baseten MCP for Machine Learning Operations

These tools allow you to list models, check deployment status, run predictions, and manage sensitive secrets directly through conversation.

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 Baseten MCP

List Models

Retrieves a list of all machine learning models managed within the Baseten account.

Get Model

Fetches detailed configuration data for one specific Baseten model ID.

Predict

Runs a serverless inference prediction by passing explicit tensor shapes or...

List Deployments

Lists all active deployment instances associated with a specific machine learning...

Get Deployment

Retrieves detailed operational information for a single, running deployment instance.

List Secrets

Displays all environment secrets configured in the workspace without revealing their actual values.

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.

Baseten 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 Baseten 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 Baseten, 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
Baseten MCP for AI Agents MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Baseten. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

VINKIUS CLOUD

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on each call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Baseten MCP: Managing ML Model Deployments with AI Agents

Right now, checking on your machine learning models is a nightmare. You're clicking between the cloud console dashboard to see if the service scaled correctly, then switching to a separate terminal window just to run a test payload against an endpoint, and finally opening a third tab to check environment variables because you forgot which API key was active. It’s slow, it requires too many hands-on clicks, and it’s impossible to audit everything in one place.

With this MCP, your agent handles the whole sequence. You tell it what needs checking—say, 'Give me status on Model X'—and it automatically pulls up deployment details, confirms the model config, and can even run a sample prediction. The result is structured, actionable data handed back to you in plain conversation.

Baseten MCP: Auditing ML Inference Infrastructure with AI Agents

Previously, verifying the operational health of an inference pipeline meant manually checking scaling rules and replica counts through multiple resource monitoring pages. If a key was missing, you had to navigate deep into the security settings just to confirm its existence.

Now, your agent manages this complexity. You can ask it to list deployments and get the specific details for any running instance in seconds. This capability moves infrastructure auditing from a half-day chore to a two-line chat command.

What Baseten MCP for AI Agents MCP does for your AI

This MCP lets you treat your AI client like a full Machine Learning Operator. Instead of jumping through dashboards or writing complex scripts, your agent handles the whole process conversationally. You can ask it to list every model currently managed by Baseten, check the status of specific deployments, and even run direct predictions using tensor inputs.

It's all about keeping your AI workflow contained, whether you’re checking secrets or running inference on a new payload.

It gives you ML-Ops control right inside your chat window. When combined with Vinkius, you get access to this functionality alongside thousands of other services, letting your agent act as the single operational hub for your entire stack.

Built · Hosted · Managed by Vinkius Baseten MCP for AI Agents — Model Deployment & Inference
Server ID 019d7558-a9f9-70f4-aef5-95adbac62678
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about Baseten MCP for AI Agents MCP

How does Baseten MCP help me manage multiple AI models? +

It centralizes your entire ML model inventory. Instead of logging into separate dashboards for each service, you can ask the agent to list all deployed models and check their statuses from one place.

Can I use Baseten MCP to test my model predictions? +

Yes, that’s a core function. You can run immediate, real-time inference tests by providing specific payloads directly to the deployed models without needing local code setup.

What if I need to check sensitive API keys or secrets? Does Baseten MCP handle that? +

The MCP lets you list all active workspace secrets. It confirms which credentials are provisioned and accessible for your models without ever showing the actual plaintext values, keeping everything secure.

Does Baseten MCP help DevOps teams audit my ML infrastructure? +

Absolutely. You can check detailed deployment information, including replica counts and autoscaling configurations, allowing you to verify that your production environment is running exactly as designed.