Baseten MCP, Ready to Go
Use Baseten MCP with Claude or Cursor to manage ML models, run inference predictions, and audit your GPU deployments from one place.
No credit card required. Experience the power of this integration risk-free.
Manage your ML-Ops deployments and inference nodes from your workspace.
Works with every AI agent you already use
…and any MCP-compatible client
How fast is the Baseten MCP Server?
Average time for the server to become ready for requests over the last 14 days, measured until the initialize / tools/list handshake completes. Metrics are updated daily between 00:00 and 04:00 UTC. Create a free account, use this MCP on Vinkius Cloud, and connect it to your AI agent in seconds.
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What AI agents can do with Baseten 6-Tool MLOps Inference Management
Use these tools to manage models, run predictions, and audit your Baseten deployment states.
List models
See all your managed models in one place. This helps you keep track of your entire model fleet.
Get model
Pull specific details for a single model. Use this to check configurations for a specific model.
Predict
Send tensor payloads or JSON to your GPU weights for a prediction. This runs inference directly.
List deployments
See active inference bounds for a specific model. It helps you see what's currently running.
Get deployment
Get the exact details of a running deployment. This is useful for auditing replica states.
List secrets
See your workspace secrets without exposing the actual values. This keeps your environment secure.
One MCP enables access. Vinkius turns MCPs into production-ready infrastructure.
You're looking at one of 5,700+ managed MCPs. The real value isn't the catalog. It's the control plane that secures, governs, audits, and manages every interaction between your agents and the tools they use.
No Shadow AI
Every agent action is visible, approved, and auditable. Nothing runs outside your governance.
Absolute agent control
Fine-grained permissions for every agent, MCP, and tool. Instantly revoke access and audit every execution.
Cost control per token
Spend broken down to the token, tool, and agent. Budgets and hard limits. No surprise invoices.
Managed & monitored infra
We operate the runtime, authentication, scaling, retries, and monitoring. Your team manages AI, not infrastructure.
Data protection, DLP by design
Sensitive data is filtered before reaching the model. Access is governed so agents receive only the information they're allowed to use.
Token optimization, real savings
Lower AI costs by delivering the right context instead of unnecessary tools. Better accuracy, faster responses, and fewer wasted tokens.
Baseten MLOps Management for Faster Model Deployment
This is for the ML engineer who is tired of jumping between the Baseten console and their IDE to check if a model is actually live or to run a quick test payload.
ML Engineer
Running test payloads against production deployments without spinning up local notebooks.
DevOps/SRE
Auditing running deployment resources and verifying replica states from a single command.
AI Researcher
Inspecting version schemas and managing inference pipeline architectures quickly.
Frequently Asked Questions
Can the Baseten MCP run my models? +
Yes, it lets your agent send payloads to your GPU weights for real-time inference. You just describe the input to your agent, and it handles the prediction call.
Does it show my secret values? +
No, it only lists the names of your secrets to keep your environment secure. It confirms they are mapped without exposing the actual keys.
Can I use this with Cursor or Claude? +
Yes, it works with any MCP-compatible client including Claude, Cursor, Windsurf, and VS Code.
How do I run a prediction using this MCP? +
Simply tell your agent what you want to predict. It will use the predict tool to send the data to your Baseten instance and show you the result.
Can it check my deployment status? +
Yes, it can pull exact details on replica states and autoscaling configurations, so you can monitor your production environment easily.
Can the AI agent run a prediction directly against my hosted model? +
Yes. By pushing a correctly formatted JSON payload to the 'predict' tool, the agent securely triggers inference on the GPU instances, returning the exact calculated response data transparently to your editor context.
Is my workspace and environmental secret data kept safe? +
Baseten secret fetching natively obscures variable values. When you use 'list_secrets', the agent simply evaluates the key names and identifiers existing across your environment to verify configurations without exposing plaintext passwords.
How do I check auto-scaling configurations for an explicitly deployed model? +
You can examine exactly how instances are managed by using 'get_deployment'. Tell the agent to target an active deployment ID and it maps the scaling limits, replica status, and container bounds out-of-the-box.
Your AI, connected to everything.
No credit card required · Free tier available
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