How to Use the Bot9 MCP in Mastra AI

Q: How do I register Bot9 tools inside a Mastra AI agent?

Run npm install @mastra/mcp@latest and initialize the MCPClient with your hosted server URL. Call mcpClient.listTools() and spread those tools directly into your Agent's tool configuration array.

Q: Can Mastra AI automatically retry failed Bot9 API calls?

Yes, Mastra's workflow engine wraps tools like sendmessage or adddatasource in retry blocks. If Bot9 experiences a temporary network hiccup, the system retries automatically using exponential backoff.

Q: How do I require human approval for Bot9 messages in Mastra AI?

Set requireToolApproval to true for the sendmessage tool in your Mastra AI configuration. This pauses the workflow and waits for an admin to greenlight the draft before sending it to the customer.

Run autonomous Bot9 support workflows with Mastra AI's resilient TypeScript agent framework.

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Resilient Bot9 Creation and Verification

Build automated setup flows in Mastra AI that create a bot using `create_bot` and verify its configuration with `get_bot`. If the Bot9 creation step hits an API hiccup, Mastra AI's workflow engine triggers automatic retries to prevent broken setups. You can define conditional logic where a failed Bot9 initialization alerts your team through a Mastra AI notification step. Spreading these Bot9 tools into your Mastra AI agent gives it full control over the lifecycle of your support bots.

Self-Healing Knowledge Base Ingestion via MCP Server

Keep Bot9 resources updated by parsing documentation with `add_data_source` within a Mastra AI pipeline. Your Mastra AI agent can periodically run `list_data_sources` to check which Bot9 URLs are active and append new ones as they change. This Bot9 MCP Server integration lets you build multi-step Mastra AI workflows that handle ingestion failures. If a Bot9 URL fails to scrape, the Mastra AI workflow retries with exponential backoff before marking the source as failed.

Autonomous Conversation Management

Scan active Bot9 support tickets using `list_conversations` and retrieve context with `get_conversation_history` in your Mastra AI workflows. The Mastra AI agent can evaluate the Bot9 history and decide whether to reply or escalate. By routing `send_message` through Mastra AI's human-in-the-loop feature, you can require manual approval before the Bot9 chatbot sends a reply. This keeps your automated Bot9 customer service safe and highly accurate within the Mastra AI ecosystem.

Setup guide

Set up Bot9 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 Bot9 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: "bot9-mcp-client",
  servers: {
    "bot9-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

const agent = new Agent({
  name: "Bot9 Agent",
  model: openai("gpt-4o"),
  instructions: "You have access to Bot9 tools.",
  tools: {
    ...(await mcpClient.listTools()),
  },
});

const result = await agent.generate(
  "List recent Bot9 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 Bot9. 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 Bot9 MCP in Mastra AI

Run `npm install @mastra/mcp@latest` and initialize the `MCPClient` with your hosted server URL. Call `mcpClient.listTools()` and spread those tools directly into your Agent's tool configuration array.

Yes, Mastra's workflow engine wraps tools like `send_message` or `add_data_source` in retry blocks. If Bot9 experiences a temporary network hiccup, the system retries automatically using exponential backoff.

Set `requireToolApproval` to true for the `send_message` tool in your Mastra AI configuration. This pauses the workflow and waits for an admin to greenlight the draft before sending it to the customer.

Yes, Mastra's client automatically detects the transport type, allowing you to connect to the hosted Bot9 endpoint over secure SSE or Streamable HTTP.

Your training sources, bot configurations, and customer conversations are fully protected. All calls go through ephemeral execution environments where credentials are encrypted and data is immediately wiped from memory after the tool executes.

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