How to Use the Cliengo MCP in Mastra AI

Q: How do I configure Mastra AI to use the Cliengo MCP Server?

Initialize it with new MCPClient({ id: "cliengo", servers: { name: { url: new URL("...") } } }). Mastra auto-detects the Streamable HTTP transport. Then call mcpClient.listTools() to inject the endpoints into your agent.

Q: Can Mastra AI require human approval for Cliengo lead updates?

You can enable requireToolApproval on specific actions. If an agent tries to modify or export sensitive records, the workflow pauses until an admin clicks approve. This keeps your automated pipelines safe.

Build resilient support workflows in Mastra AI using live Cliengo lead and chat data.

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Connect Cliengo MCP to Mastra AI

Create your Vinkius account to connect Cliengo 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 Cliengo with Mastra AI

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Perplexity

Automate lead routing via MCP Server

The `list_cliengo_leads` tool feeds directly into your Mastra AI conditional branches. If a new contact matches a high-value criteria, your workflow automatically routes them to a specific sales tier. Drilling down relies on `get_lead_details`. Your agent pulls the exact metadata, and if the API times out, Mastra's built-in exponential backoff handles the retry automatically.

Extract and sync chat transcripts

Running `get_chat_history` through the MCP pulls the exact dialogue from any customer interaction. You can configure a workflow that triggers whenever a chat ends, dumping the transcript into your CRM. Tracking specific user interactions requires `get_contact_messages`. Mastra AI monitors these threads and executes a fallback branch if the customer expressed frustration in the text.

Monitor webhook health

Checking your real-time data pipelines is done with the `list_cliengo_webhooks` tool on this MCP Server. A scheduled Mastra agent verifies that your lead forwarding rules remain active across all environments. Verifying deployment status uses `list_cliengo_websites`. If a widget goes offline, your workflow catches the missing domain and alerts the engineering team before marketing notices.

Setup guide

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

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

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

Initialize it with `new MCPClient({ id: "cliengo", servers: { name: { url: new URL("...") } } })`. Mastra auto-detects the Streamable HTTP transport. Then call `mcpClient.listTools()` to inject the endpoints into your agent.

You can enable `requireToolApproval` on specific actions. If an agent tries to modify or export sensitive records, the workflow pauses until an admin clicks approve. This keeps your automated pipelines safe.

The framework uses automatic retries with exponential backoff. If you hit a limit while looping through `list_chat_conversations`, the agent backs off and tries again without crashing the run.

You build a fallback branch in your workflow. The agent tries the primary sync, catches the failure, and executes an alternative notification step.

Your AI client reads direct conversational transcripts and user identities. The Vinkius zero-trust architecture ensures this connection is strictly ephemeral. No chat history is cached or logged on our infrastructure.

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