How to Use the Bland AI MCP in Mastra AI

Q: Can Mastra AI handle conditional branching based on Bland AI call outcomes?

Yes, you can inspect the results of analyzecalltranscript within a Mastra AI workflow. Based on the Bland AI sentiment score, your Mastra workflow can branch to send an email or trigger another call.

Q: Do I need to manually approve Bland AI voice agent deletions in Mastra AI?

You can enable requireToolApproval in Mastra AI before executing destructive actions. This forces a human-in-the-loop check before your Mastra agent can run deletevoiceagent on Bland AI.

Build resilient voice workflows in Mastra AI with retries and conditional Bland AI phone routing.

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Connect Bland AI MCP to Mastra AI

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Setup Bland AI with Mastra AI

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Resilient call routing with Mastra AI workflows

Build complex voice funnels that survive API hiccups by hooking Bland AI's `send_phone_call` into a Mastra AI workflow. This lets you set up automatic retries with exponential backoff if a Bland AI call fails to connect. The Mastra AI workflow engine monitors the Bland AI call status dynamically. If `list_recent_calls` shows a failed attempt, Mastra routes the next try to an alternative Bland AI phone number from `list_phone_numbers`.

Conditional agent updates via Mastra AI MCP Server

Automate how your Bland AI phone agents adapt to live customer data using this MCP Server. Mastra AI agents evaluate customer history and run `update_agent_config` to change Bland AI prompt scripts before triggering a call. This setup lets you branch your Mastra AI logic based on Bland AI profiles. If a customer is flagged as high-value, the Mastra workflow switches the Bland AI agent's voice using `list_available_voices` to match their profile.

Automated post-call analysis and escalation

Create multi-step Mastra AI pipelines that trigger immediately after a Bland AI conversation ends. Mastra AI pulls the conversation data using `get_call_details` and runs `analyze_call_transcript` to scan for negative sentiment. If the Mastra AI analysis detects an unhappy customer on the Bland AI line, the workflow branches. It immediately alerts your team or schedules a follow-up call using `send_phone_call` via Mastra.

Setup guide

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

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

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

Initialize the Mastra AI client and register the Bland AI MCP Server in your configuration. You can then spread `mcpClient.listTools()` directly into your Mastra AI agent's tool array.

Yes, you can inspect the results of `analyze_call_transcript` within a Mastra AI workflow. Based on the Bland AI sentiment score, your Mastra workflow can branch to send an email or trigger another call.

Mastra AI uses its built-in workflow engine to handle Bland AI API timeouts. If a tool like `send_phone_call` fails, the Mastra engine executes automatic retries using backoff rules you define.

You can enable `requireToolApproval` in Mastra AI before executing destructive actions. This forces a human-in-the-loop check before your Mastra agent can run `delete_voice_agent` on Bland AI.

Your Bland AI voice agent configurations and call details are processed inside isolated MCP sandboxes. Vinkius secures these credentials and never persists your Mastra AI keys or call transcripts.

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