How to Use the Endorsal Testimonials MCP in Mastra AI

Q: How do I trigger an Endorsal Testimonials search in Mastra AI?

Use searchtestimonialsbykeyword as a tool in your Mastra AI agent definition. It allows for quick lookups during complex multi-step workflows.

Q: Can Mastra AI handle bulk approvals for Endorsal Testimonials?

Yes. You can loop through the results of listpendingtestimonials and call approvependingtestimonial for each item within your agent workflow.

Q: Does this MCP server work with Mastra AI's human-in-the-loop features?

Absolutely. You can set requireToolApproval on the approval tools to ensure a human reviews every testimonial before it goes live.

Build complex testimonial workflows in Mastra AI with automatic retries and conditional logic for Endorsal Testimonials.

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Connect Endorsal Testimonials MCP to Mastra AI

Create your Vinkius account to connect Endorsal Testimonials 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 Endorsal Testimonials with Mastra AI

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Conditional testimonial branching in Mastra AI

Create workflows that decide whether to publish a review based on its content. Your agent uses `get_testimonial_details` to analyze the text before deciding to call `approve_pending_testimonial`. This logic ensures only the highest quality feedback reaches your public widgets. It turns a manual task into a reliable, automated pipeline.

Manage account properties with Mastra AI

Track multiple brands or websites by using `list_account_properties`. Your agent identifies which property a testimonial belongs to and routes it accordingly. This is essential for agencies or multi-brand companies. It keeps your data organized and ensures the right reviews hit the right pages.

Automatic error handling for Endorsal operations

Mastra AI handles transient failures when calling `list_all_testimonials`. If the API is busy, the framework automatically retries the operation with backoff. This makes your agents resilient. You don't have to write custom error-catching code for every single interaction.

Setup guide

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

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

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

Use `search_testimonials_by_keyword` as a tool in your Mastra AI agent definition. It allows for quick lookups during complex multi-step workflows.

Yes. You can loop through the results of `list_pending_testimonials` and call `approve_pending_testimonial` for each item within your agent workflow.

The server enforces authentication via your API key. Mastra AI keeps all tool execution logs within your specified environment, preventing unauthorized data leakage.

Absolutely. You can set `requireToolApproval` on the approval tools to ensure a human reviews every testimonial before it goes live.

It accesses your public and pending review text, customer metadata, and widget configurations. All data is encrypted in transit using standard HTTPS protocols.

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