How to Use the Mention MCP in Mastra AI

Q: Can Mastra AI automate responses using Mention data?

Absolutely. You chain searchmentions into an agent task, then use the output to draft responses. It is the fastest way to handle high-volume social inquiries.

Q: Is it easy to filter noisy alerts in Mastra AI?

Yes. You query getalertstatistics first to identify high-activity alerts. Then you only process the listmentions output for those specific, relevant alerts.

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Connect Mention MCP to Mastra AI

Create your Vinkius account to connect Mention 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 Mention with Mastra AI

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Automated alert workflows in Mastra AI

Create conditional logic that triggers when `get_alert_statistics` shows a spike in activity. If the volume passes your threshold, your Mastra AI agent can automatically notify your team. Handle failures by wrapping your calls in retry logic. Since this MCP Server provides clean JSON, your workflow engine can parse the output of `list_alerts` without custom scrapers.

Deep sentiment analysis with Mastra AI

Route specific posts to an analysis agent using `get_mention_details`. You can build a pipeline that flags negative sentiment for immediate human review. Scale your monitoring by batching requests. Use `list_mentions` to gather raw data, then let your Mastra AI agents categorize the intent of each post.

Manage account access for Mastra AI

Audit your monitoring coverage by calling `list_account_users`. This ensures your agents are only acting on data authorized by your team members. Check your integration health with `list_connected_external_accounts`. Your workflows will fail gracefully if the underlying social accounts disconnect, keeping your automation stable.

Setup guide

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

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

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

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Why Choose Vinkius

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Common questions about Mention MCP in Mastra AI

Absolutely. You chain `search_mentions` into an agent task, then use the output to draft responses. It is the fastest way to handle high-volume social inquiries.

The MCP Server returns an error that Mastra AI can catch. You then implement exponential backoff in your workflow to wait before retrying the fetch.

The server operates in a sandbox. It only accesses the specific alert and mention data you request, keeping your account's broader configuration locked down.

Yes. You query `get_alert_statistics` first to identify high-activity alerts. Then you only process the `list_mentions` output for those specific, relevant alerts.

Just the URL and the server definition. Once defined in your Mastra AI agent config, the tools are ready to be called in your workflow steps.

Use it with your favorite AI tools

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