How to Use the Moneypenny MCP in Mastra AI

Q: Can I filter Moneypenny logs by date in Mastra AI?

Absolutely. The listchatlogs tool accepts ISO 8601 timestamps, allowing your agents to define specific ranges for their data processing tasks.

Build resilient communication workflows in Mastra AI with automated retry logic and direct tool execution.

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Connect Moneypenny MCP to Mastra AI

Create your Vinkius account to connect Moneypenny 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 Moneypenny with Mastra AI

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Automated workflow triggers

Integrate reception logs into your multi-step Mastra AI pipelines. Using `get_this_week_calls` allows your agents to trigger follow-up actions based on recent customer activity. If a call record appears, your agent can decide to archive it or draft a response. The workflow engine handles the execution flow while the server provides the raw data.

Conditional conversation handling

Use `get_recent_chats` to feed your conditional branching logic. You can build agents that route high-priority chats to specific team members based on the content retrieved. This keeps your operations moving without manual intervention. The integration handles the heavy lifting of polling the API so your agent focuses on decision-making.

Reliable data fetching

Ensure your agents always have the latest information using `get_activity_summary`. This provides a high-level view of daily performance that informs how your agents prioritize their tasks. It is perfect for scheduled agent runs that need a quick pulse check on the business. You get a clean summary without parsing through individual logs every time.

Setup guide

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

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

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

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

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Common questions about Moneypenny MCP in Mastra AI

You add the server URL to your Mastra client configuration. After that, your agent can list the tools and use them within any workflow step.

Yes, you can configure your workflow steps to retry if a tool call fails. This is standard for any MCP server integrated into your agent framework.

You gain the ability to chain communication data into complex actions. Your agent can read a chat log and update your CRM in one go.

All traffic is handled through encrypted endpoints. Your chat logs and phone records pass through the connection directly to your agent environment.

Absolutely. The `list_chat_logs` tool accepts ISO 8601 timestamps, allowing your agents to define specific ranges for their data processing tasks.

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

Mastra AI sdk-typescript

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