How to Use the TrueFoundry MCP in Mastra AI

Q: How does TrueFoundry integrate with Mastra AI?

You simply list the necessary tools using mcpClient.listTools() and pass them directly into your agent's toolset. Mastra AI auto-detects the transport, making setup quick.

Q: Can I use TrueFoundry for embedding within Mastra AI?

Yes. You call truefoundrygenerateembeddings to calculate semantic vectors needed by your workflows. These vectors can then drive conditional logic or data lookup steps.

Q: Does TrueFoundry support human oversight with Mastra AI?

Mastra AI supports requireToolApproval for human-in-the-loop workflows. This means complex or high-risk actions, like deploying a new service, require explicit user sign-off.

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Connect TrueFoundry MCP to Mastra AI

Create your Vinkius account to connect TrueFoundry 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.

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Setup TrueFoundry with Mastra AI

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Perplexity

Execute Multi-Step Workflows via MCP Server

Mastra AI lets you build complex operational sequences. If a step fails (like a payment denial), the workflow engine automatically retries with exponential backoff or branches to an admin notification path. You connect TrueFoundry's tools—such as `truefoundry_list_mcp_servers`—into your agent actions, making them part of a robust, stateful process.

Control Model Access and Initialization

You can use `truefoundry_get_mcp_server_info` to grab the exact JSON metadata for any registered tool schema. This gives your workflow engine precise control over what tools are available. Need to start a new service? Call `truefoundry_deploy_mcp_server` to spawn the backend container logical process, and Mastra AI manages its lifecycle.

Handle Complex Tool Orchestration

The MCP Server provides tools like `truefoundry_list_deployments` that give your workflow visibility into existing topologies. You don't just run a single function; you monitor the whole environment. Mastra AI integrates this monitoring, allowing conditional logic based on deployment status metrics.

Setup guide

Set up TrueFoundry 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 TrueFoundry 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: "truefoundry-mcp-client",
  servers: {
    "truefoundry-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

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

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Common questions about TrueFoundry MCP in Mastra AI

You simply list the necessary tools using `mcpClient.listTools()` and pass them directly into your agent's toolset. Mastra AI auto-detects the transport, making setup quick.

Yes. You call `truefoundry_generate_embeddings` to calculate semantic vectors needed by your workflows. These vectors can then drive conditional logic or data lookup steps.

This server primarily handles deployment metadata and tool schemas. You deal with the JSON structure defining these tools, which is crucial for building your workflows.

Absolutely. The combination of MCP Server tools and Mastra AI's workflow engine allows you to build sophisticated fail-safe operations, like automatic retries after an external API fails.

Mastra AI supports `requireToolApproval` for human-in-the-loop workflows. This means complex or high-risk actions, like deploying a new service, require explicit user sign-off.

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