Bring Model Deployment
to LangChain
Create your Vinkius account to connect Baseten to LangChain and start using all 6 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Baseten MCP Server?
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
- Subscribe to this server
- Enter your Baseten API Key
- 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
Built-in capabilities (6)
Get 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
Why LangChain?
LangChain's ecosystem of 500+ components combines seamlessly with Baseten through native MCP adapters. Connect 6 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
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The largest ecosystem of integrations, chains, and agents. combine Baseten MCP tools with 500+ LangChain components
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Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
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LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
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Memory and conversation persistence let agents maintain context across Baseten queries for multi-turn workflows
Baseten in LangChain
Why run Baseten with Vinkius?
The Baseten connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 6 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect Baseten using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
Baseten and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect Baseten to LangChain through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
Baseten for LangChain
Every request between LangChain and Baseten is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
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.
How does LangChain connect to MCP servers?
Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
Which LangChain agent types work with MCP?
All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
Can I trace MCP tool calls in LangSmith?
Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.
MultiServerMCPClient not found
Install: pip install langchain-mcp-adapters
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