How to Use the AntEater MCP in Mastra AI

Q: Where is my contact history data stored during workflow execution?

The contact details fetched via getcontacthistory exist purely in-memory within the V8 sandbox. Once the Mastra workflow step completes, the sandbox is destroyed and no data remains.

Build resilient Mastra AI workflows that trigger actions based on AntEater contact updates and team activity.

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Connect AntEater MCP to Mastra AI

Create your Vinkius account to connect AntEater 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 AntEater with Mastra AI

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Automate contact-driven workflows with Mastra AI

Running the `list_contacts` tool allows your Mastra AI agent to pull your entire shared directory to evaluate workflow triggers. When a new contact is added, the engine can automatically run conditional checks to categorize them. If a contact lookup fails, Mastra's built-in retry logic executes exponential backoff before alerting your team. This ensures your customer database syncs perfectly even during minor API hiccups.

Multi-step team activity tracking via MCP Server

Integrating `search_activity` into your Mastra workflow steps lets you scan email and Slack logs for specific keywords. You can build paths that branch based on whether a client was emailed in the last 24 hours. By chaining `get_contact_history` after the search, your agent can automatically draft follow-up tasks. The workflow engine manages these multi-step transitions without losing state.

Human-in-the-loop approvals for contact modifications

Before making directory changes, the `get_profile` tool identifies the active user to enforce security. You use Mastra's approval gates to halt the workflow until an authorized team member signs off. This setup prevents your agent from making unauthorized updates to your directory. It combines `get_user` data with Mastra's state machine to keep your records clean and verified.

Setup guide

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

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

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

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Common questions about AntEater MCP in Mastra AI

Install the Mastra MCP package and declare the server URL in your configuration. You then call `listTools()` on the client and spread those tools directly into your agent's tool definition array.

Yes, Mastra's workflow engine uses automatic retries to handle rate limits during heavy `list_recent_activity` runs. It pauses and retries without crashing your active run.

It works perfectly with it. You can require manual approval in Mastra before the agent executes tools like `search_contacts` to protect sensitive directory searches.

It supports both SSE and Streamable HTTP. Mastra automatically detects the transport type from your Vinkius URL, so you do not have to write custom connection adapters.

The contact details fetched via `get_contact_history` exist purely in-memory within the V8 sandbox. Once the Mastra workflow step completes, the sandbox is destroyed and no data remains.

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