How to Use the Loopio MCP in Mastra AI

Q: How does Mastra AI handle Loopio tool errors?

You configure retry policies in your agent definition. If searchlibrary times out, it tries again based on your settings. This ensures your RFP automation stays reliable.

Q: Can I use Mastra AI to manage Loopio projects?

Absolutely. You list all projects with listprojects and feed the output into your workflow. It allows your agents to decide which RFP needs priority attention.

Build resilient RFP workflows in Mastra AI. Automate complex response chains with built-in retry logic and state management.

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Connect Loopio MCP to Mastra AI

Create your Vinkius account to connect Loopio 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 Loopio with Mastra AI

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Automate response chains in Mastra AI

Chain `search_library` and `create_submission` inside your agent workflows. If an API call fails, the framework handles the retry automatically so your RFP process doesn't stall. You define the logic flow once. The agent handles the back-and-forth until the questionnaire is ready for review.

Monitor RFP status with MCP Server

Use `get_project` to track progress across your team. You can set up conditional branches that notify admins when a high-value RFP moves to a new stage. This keeps your pipeline moving without manual oversight. You gain full control over the lifecycle of every questionnaire.

Sync team members with Mastra AI

Call `list_team_members` to ensure ownership is assigned correctly. You can program the agent to reassign tasks if the current owner is inactive. It makes internal coordination predictable. Your agents act on the latest workspace data to prevent bottlenecks.

Setup guide

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

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

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

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Common questions about Loopio MCP in Mastra AI

You configure retry policies in your agent definition. If `search_library` times out, it tries again based on your settings. This ensures your RFP automation stays reliable.

Absolutely. You list all projects with `list_projects` and feed the output into your workflow. It allows your agents to decide which RFP needs priority attention.

The server uses a dedicated endpoint token for all operations. Your sensitive RFP content stays encrypted in transit. We isolate every interaction to your specific workspace.

You can force a human-in-the-loop check using the framework's approval feature. The agent pauses after calling `get_questionnaire_responses` until a person confirms the draft.

Yes, you can write custom handlers for the results. Just pass the output of any tool into your own functions. It gives you full control over how your agent behaves.

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