How to Use the LinkedIn Ads MCP in Mastra AI

Q: How do I manage LinkedIn Ads failures in Mastra AI?

Configure your agent with retry logic. If a call to getadanalytics fails, the framework waits and tries again before alerting you.

Q: Can I chain LinkedIn Ads tools in Mastra AI?

Absolutely. You can pass the output of listadaccounts directly into listadcampaigns to scope your analysis.

Build resilient LinkedIn Ads workflows in Mastra AI with automatic retries and conditional logic.

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Connect LinkedIn Ads MCP to Mastra AI

Create your Vinkius account to connect LinkedIn Ads 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 LinkedIn Ads with Mastra AI

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Automated LinkedIn Ads reporting in Mastra AI

Set up agents that check performance on a schedule. Using `get_ad_analytics`, the agent can pull numbers and decide if a campaign needs a budget shift. If the API response is delayed, the framework handles the retry logic automatically. Your workflows keep running without manual intervention.

Complex campaign management for Mastra AI

Chain multiple operations together. Start by calling `list_ad_accounts` to find the target, then iterate through `list_ad_campaigns` to audit status. This creates a clear sequence of events. You can branch your logic based on the output of each specific tool.

Conversion tracking for Mastra AI

Verify your setup by pulling active rules with `list_conversion_rules`. Your agent can compare these against your internal database. Errors get caught early. If a rule is missing, your workflow can trigger a notification to the team immediately.

Setup guide

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

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

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

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Common questions about LinkedIn Ads MCP in Mastra AI

Yes, you add the tools to your agent definition. It then handles the interaction with the LinkedIn API endpoints.

Configure your agent with retry logic. If a call to `get_ad_analytics` fails, the framework waits and tries again before alerting you.

Absolutely. You can pass the output of `list_ad_accounts` directly into `list_ad_campaigns` to scope your analysis.

Your credentials never leave your infrastructure. The server process manages the requests securely.

It accesses your ad account IDs, campaign names, creative assets, and conversion rule definitions. It does not store this data; it only passes it to your agent.

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