How to Use the Cerebras Inference MCP in Mastra AI

Q: How do I use Cerebras Inference tools within a Mastra AI workflow?

After creating your MCPClient, call mcpClient.listTools() and spread the result into your Mastra Agent's toolset. The agent can then invoke tools like createbatch as steps in its workflow.

Q: Does Mastra AI support human-in-the-loop for Cerebras Inference tasks?

It does. Set requireToolApproval to true in your agent's configuration. Before the agent executes a destructive tool like deletefile or a costly one like createbatch, it will pause for human confirmation.

Build resilient inference workflows on Cerebras with Mastra AI. Automate batch processing, retries, and conditional logic.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Cerebras Inference MCP to Mastra AI

Create your Vinkius account to connect Cerebras Inference to Mastra AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Cerebras Inference with Mastra AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Unbreakable Batch Processing

Create complex batch processing pipelines with Mastra AI's workflow engine. Start by uploading a dataset with `upload_file`, then trigger a job with `create_batch`. Mastra's engine handles the state for you. If a `get_batch` call fails, Mastra can automatically retry with exponential backoff. You can build conditional logic: if the job status is 'completed', fetch the results with `get_file_content`; if 'failed', send a notification.

Dynamic Model-Aware Agents

Your Mastra agent can start by checking what's available. It calls `list_models` to see the current Cerebras models, then uses `get_model` to check a specific model's parameters before deciding which one to use for a task. This makes your workflows more dynamic. Instead of hardcoding a model name, the agent can choose the best fit based on real-time availability and capabilities, then execute `create_completion` or `create_chat_completion`.

Full Lifecycle Management with a Mastra AI MCP Server

This MCP Server gives your agent full control. It can list existing files with `list_files`, check on jobs with `list_batches`, and clean up after itself using `delete_file` and `cancel_batch`. You can even build monitoring workflows. Have an agent periodically call `get_metrics` to check the server's operational health and pipe that data into your own systems. It's about building agents that manage their own tools.

Setup guide

Set up Cerebras Inference MCP in Mastra AI

Prerequisites

Node.js 18+ and a TypeScript project
@mastra/mcp + @mastra/core packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run npm install @mastra/mcp @mastra/core plus your preferred model provider (e.g. @ai-sdk/openai).
2

Configure the MCPClient
Create an MCPClient with your Vinkius endpoint as a URL object. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Discover and inject tools
Call mcpClient.listTools() and spread the result into your agent's tools object. All Cerebras Inference tools become native Mastra tools.
4

Run with any model
Swap openai("gpt-4o") for any AI SDK-compatible provider. Call agent.generate() and the agent routes tool calls through MCP automatically.

agent.ts

import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";

const mcpClient = new MCPClient({
  id: "cerebras-inference-mcp-client",
  servers: {
    "cerebras-inference-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Cerebras Inference Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Cerebras Inference tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Cerebras Inference transactions"
);
console.log(result.text);

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Cerebras Inference. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Cerebras Inference now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Cerebras Inference MCP in Mastra AI

After creating your MCPClient, call `mcpClient.listTools()` and spread the result into your Mastra Agent's toolset. The agent can then invoke tools like `create_batch` as steps in its workflow.

Yes, that's what it's for. You can configure automatic retries on tools like `get_batch`. You can also define conditional branches, so if a `create_chat_completion` call fails, the workflow can try a different model or alert a human.

It does. Set `requireToolApproval` to true in your agent's configuration. Before the agent executes a destructive tool like `delete_file` or a costly one like `create_batch`, it will pause for human confirmation.

Mastra has a one-command deploy for cloud environments. Your agent, its workflow definition, and its connection to the Cerebras Inference MCP server are all bundled together for deployment.

The files are stored securely on the Vinkius-managed server. Each request is handled in a zero-trust, ephemeral environment. You have explicit control to remove your data using the `delete_file` tool once your batch job is done.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript