How to Use the Chatsistant MCP in Mastra AI

Q: How do I make a Chatsistant tool available to my Mastra AI agent?

First, you instantiate the MCPClient with your Vinkius URL. Then you call mcpClient.listTools() and spread the result into the tools array when you define your Mastra Agent.

Q: Does Mastra AI require human approval before my agent modifies a Chatsistant bot?

You can set that up. Mastra supports a requireToolApproval flag that pauses the workflow before a sensitive operation like adddatasource runs. An admin then has to approve it before the agent can proceed.

Automate customer support operations and build resilient bot management workflows with Chatsistant and Mastra AI.

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Connect Chatsistant MCP to Mastra AI

Create your Vinkius account to connect Chatsistant 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 Chatsistant with Mastra AI

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Perplexity

Build Self-Healing Bot Workflows

The `query_bot` tool lets your Mastra agent get answers from a knowledge base. If the query fails or times out from a network blip, Mastra's built-in retry logic can try again with exponential backoff. You don't have to write any of that boilerplate code. This lets you build much more complex chains. For example: `query_bot`, and if the answer includes the word 'escalate', use another tool to create a support ticket. Mastra handles the state and conditional logic between steps.

Automated Bot Provisioning and Updates

You can create real operational workflows. A Mastra agent can use `list_bots` to check if a new client has a bot provisioned yet. If not, it can trigger an alert for an admin to create one. Or, you can use `add_data_source` to automatically update a bot's knowledge base as part of a CI/CD pipeline. Your agent can pull new docs from a git repository, then feed them to the correct bot, all within one Mastra workflow.

Your Mastra AI MCP Server for Support Ops

This isn't just for one-off tasks. You can combine `list_conversations` and `get_conversation` to build a monitoring agent. Your Mastra workflow can periodically scan new conversations for negative sentiment or specific keywords. When a problem is found, the workflow branches. It might use `list_webhooks` to check if a Slack notification is configured, and if not, send an email instead. Mastra manages the entire decision tree for you.

Setup guide

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

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

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

First, you instantiate the `MCPClient` with your Vinkius URL. Then you call `mcpClient.listTools()` and spread the result into the `tools` array when you define your Mastra Agent.

Yes, that's handled automatically by the workflow engine. If a call to `get_bot` fails, Mastra will retry it with exponential backoff. You get resilience without writing extra code.

You can set that up. Mastra supports a `requireToolApproval` flag that pauses the workflow before a sensitive operation like `add_data_source` runs. An admin then has to approve it before the agent can proceed.

Think about backend operational tasks. You can build agents that monitor conversation quality, automatically update knowledge bases from external sources, or run nightly checks for misconfigured bots using tools like `list_data_sources`.

Your credentials stay secure. The Vinkius MCP server endpoint uses a single token for auth, so your actual Chatsistant keys are never part of the workflow. All data in transit, like conversation content or bot IDs, is processed in a zero-trust environment and is not logged by Vinkius.

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