How to Use the ChatFly MCP in Mastra AI

Q: How does Mastra AI handle errors during ChatFly uploads?

Mastra uses built-in retry logic, so if uploaddatasource fails due to a temporary network glitch, the workflow will pause and try again.

Build reliable support agent workflows that auto-retry bot creation and recover from failed data uploads using Mastra AI.

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…and any MCP-compatible client

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Connect ChatFly MCP to Mastra AI

Create your Vinkius account to connect ChatFly 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 ChatFly with Mastra AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Bulletproof bot creation

Your workflows can trigger the `create_bot` tool and automatically retry the action with exponential backoff if a network error occurs. This ensures your automated customer onboarding pipelines don't break halfway through. You get a workflow that runs in the background and only alerts your team if it fails repeatedly.

Smart knowledge base updates

Chaining the `list_data_sources` tool before you ingest files lets your agent verify what is already loaded. Mastra allows you to branch your logic so that if a data source is already present, you trigger `update_bot` instead of duplicating files. This keeps your agent's knowledge base clean and cost-efficient.

Automated agent auditing via MCP Server tools

Scheduling a workflow to run `list_bots` allows your system to audit active customer agents on a set interval. By feeding mock queries into `chat` and analyzing the response, your system can automatically flag agents that return stale information. You build a self-healing monitoring loop with zero manual oversight.

Setup guide

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

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

const result = await agent.generate(
  "List recent ChatFly 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 ChatFly. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect ChatFly now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about ChatFly MCP in Mastra AI

Absolutely. You can write a Mastra workflow that loops through a list of configurations, calls `create_bot` for each, and then registers them inside your central database.

Mastra uses built-in retry logic, so if `upload_data_source` fails due to a temporary network glitch, the workflow will pause and try again.

Yes, you can set up Mastra to require manual approval before your agent executes `update_bot` or modifies any live production configurations.

You initialize the MCP client pointing to the Vinkius endpoint, fetch the tool definitions, and spread them directly into the agent's tool array. The agent can then choose when to run `chat` or retrieve bot lists dynamically.

Your API tokens and bot configurations are never exposed to the Mastra runtime or logged in plain text. All communications with this MCP Server go through encrypted channels, keeping your internal customer service data completely private.

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