How to Use the FirstQuadrant MCP in Mastra AI

Q: Can I build loops with FirstQuadrant and Mastra AI?

Absolutely. You can iterate through lists from listcontacts and apply logic to each record until your criteria are met.

Automate complex sales workflows in Mastra AI. Build resilient pipelines with FirstQuadrant tools and handle errors through code.

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Connect FirstQuadrant MCP to Mastra AI

Create your Vinkius account to connect FirstQuadrant 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 FirstQuadrant with Mastra AI

Ask AI about this MCP

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Claude

Perplexity

Workflow-driven prospecting

Orchestrate multi-step sequences by chaining `create_contact` and `enrich_contact_ai`. Mastra AI handles the state, ensuring that if one step fails, the workflow catches it. Define your logic branches based on lead quality. You can set up automatic retries for failed enrichment requests without writing custom error handlers.

Conditional campaign routing

Use `list_campaigns` to decide where a lead goes based on its profile. If the enrichment data meets your criteria, the agent executes `add_to_campaign` automatically. Build self-healing pipelines that adjust to your sales volume. The agent monitors `list_activities` to confirm enrollment success before moving to the next task.

Custom property management

Sync your CRM schema using `list_properties_schema` within your Mastra workflows. This ensures the agent always knows the current structure of your lead records. Maintain data integrity by validating contact inputs before calling `create_contact`. Your agent acts as a gatekeeper for your sales data.

Setup guide

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

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

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

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Common questions about FirstQuadrant MCP in Mastra AI

Import the client and spread the tools into your agent configuration. Mastra recognizes the tool definitions, allowing you to call them in any step.

It does. You can enable human-in-the-loop approvals for sensitive actions like `add_to_campaign` to ensure you vet leads before outreach.

Absolutely. You can iterate through lists from `list_contacts` and apply logic to each record until your criteria are met.

Mastra handles retries with exponential backoff. Your workflow waits for the cooldown and picks up right where it left off.

Your workflow environment remains isolated. We use ephemeral sessions to process your lead contact details, preventing any persistence outside of your CRM.

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