Baseten MCP Server
Manage your Baseten AI models — orchestrate deployments, list secrets, and run serverless inference predictions autonomously.
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What is the Baseten MCP Server?
The Baseten MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Baseten via 6 tools. Manage your Baseten AI models — orchestrate deployments, list secrets, and run serverless inference predictions autonomously. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (6)
Tools for your AI Agents to operate Baseten
Ask your AI agent "List standard machine learning models we currently host on Baseten." and get the answer without opening a single dashboard. With 6 tools connected to real Baseten data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
Baseten MCP Server capabilities
6 toolsGet explicit details of a running deployment
Get a specific Baseten model
List active inferences bounds matching a specific model
List Baseten managed models
List securely managed workspace secrets without showing values
Formulate the explicit tensor shapes or dictionaries strictly matching the deployed instance. Invoke a serverless model inference prediction
What the Baseten MCP Server unlocks
Connect your Baseten account to any AI agent and track, deploy, and execute your machine learning models through natural conversation.
O que você pode fazer
- Model Management — List managed models, fetch configurations, and understand active routing boundaries
- Serverless Deployments — Inspect exact replica states, autoscaling configurations, and deployment versions
- Inference Execution — Run direct predictions (
predict) pushing tensor payloads or JSON directly to GPU weights - Workspace Secrets — Enumerate active environment secrets securely mapped inside the isolated orchestration ecosystem
Como funciona
1. Subscribe to this server
2. Enter your Baseten API Key
3. Gain complete ML-Ops control over your active inference nodes using Claude, Cursor, or your preferred agent
Scale unified AI infrastructure without bouncing between terminal windows. Your agent becomes a capable Machine Learning Operator tracking your GPU lifecycle.
Para quem é?
- ML Engineers — execute test payloads to deployments instantaneously without spinning up local Python notebooks
- DevOps/SREs — audit running deployment resources and verify replica states reliably from your core IDE
- AI Researchers — inspect version schemas and manage inference pipeline architectures quickly
Frequently asked questions about the Baseten MCP Server
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.
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Connect Baseten with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Give your AI agents the power of Baseten MCP Server
Production-grade Baseten MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.