How to Use the HeyReach MCP in Mastra AI

Q: How do I inject leads using this MCP integration?

Your agent calls addleadstocampaign and passes the required leadsjson string. You just need to supply the target campaignId fetched from listcampaigns.

Build resilient LinkedIn outreach workflows with Mastra AI, adding automatic retries and conditional branching to your HeyReach operations.

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Connect HeyReach MCP to Mastra AI

Create your Vinkius account to connect HeyReach 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 HeyReach with Mastra AI

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Run resilient HeyReach MCP Server workflows

The `list_linkedin_accounts` tool checks sender availability before Mastra AI routes any outbound messages. If an account hits a rate limit, the workflow engine automatically retries the operation with exponential backoff using a different connected profile. You build complex sequences that handle failure gracefully. The agent verifies the API key via `get_api_profile` and halts the entire outreach pipeline if the credentials fail, alerting an admin instead of crashing.

Branch campaign logic based on lead status

Your workflow calls `list_lead_campaigns` to check if a prospect is already receiving messages. Mastra AI evaluates this array and branches: skip the lead if active, or proceed if they are clear for new outreach. For clear prospects, the agent triggers `add_leads_to_campaign` with the JSON payload. If the campaign is inactive, the workflow catches the error, runs `resume_campaign`, and tries the injection again.

Control automated LinkedIn messaging safely

The `send_linkedin_message` tool dispatches automated replies to active threads found via `list_conversations`. Mastra AI lets you wrap this action with requireToolApproval so a human reviews the drafted message before it hits LinkedIn. If a prospect responds negatively, the workflow engine immediately executes `pause_campaign` for that specific sequence. The agent logs the interaction and safely stops further automated follow-ups.

Setup guide

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

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

const result = await agent.generate(
  "List recent HeyReach 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 HeyReach. 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 HeyReach MCP in Mastra AI

Instantiate MCPClient with your server URL and call mcpClient.listTools(). Spread those tools directly into your Agent configuration to enable LinkedIn automation.

Yes. You can build a workflow that monitors reply rates via `list_conversations` and triggers `pause_campaign` if negative sentiment crosses a specific threshold.

It handles them perfectly. The built-in workflow engine uses exponential backoff to retry `get_lead_details` or message sends if the LinkedIn API throttles your workspace.

Your agent calls `add_leads_to_campaign` and passes the required leads_json string. You just need to supply the target campaignId fetched from `list_campaigns`.

The framework requests conversation histories and profile JSON payloads strictly for workflow evaluation. The MCP Server operates inside an ephemeral sandbox, meaning your private messages vanish from the server the millisecond the workflow step completes.

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