How to Use the BLS Public Data API MCP in Mastra AI

Build resilient economic workflows in Mastra AI using real-time labor data from the BLS Public Data API.

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Connect BLS Public Data API MCP to Mastra AI

Create your Vinkius account to connect BLS Public Data API 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 BLS Public Data API with Mastra AI

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Perplexity

Check BLS Public Data API availability in Mastra AI

Use `check_api_status` as a conditional step in your agent workflow. If the service is unreachable, your Mastra agent can trigger an error handler or pause execution. This keeps your multi-step pipelines from crashing due to unexpected downtime. It acts as a gatekeeper for your downstream logic.

Automate series data retrieval

Include `get_bls_timeseries_data` in your agent tools to pull historical labor stats on demand. The agent automatically parses the results and moves to the next task. You can set up exponential backoff if the API hits a rate limit. It ensures your data-gathering agents are persistent and self-correcting.

Human-in-the-loop tool approval

Mastra AI supports requiring your authorization before the server executes a tool. You verify the series IDs before the agent pulls the numbers. This gives you total oversight of what data your agents touch. It balances autonomous operation with your final review.

Setup guide

Set up BLS Public Data API 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 BLS Public Data API 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: "bls-public-data-api-mcp-client",
  servers: {
    "bls-public-data-api-mcp": {
      url: new URL(
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
      ),
    },
  },
});

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

const result = await agent.generate(
  "List recent BLS Public Data API transactions"
);
console.log(result.text);

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Common questions about BLS Public Data API MCP in Mastra AI

You instantiate the client with the Vinkius URL and spread the tools into your agent definition. The framework handles the tool signatures and calling logic.

Absolutely, you can inspect the tool output within your workflow code. If the labor data hits a specific threshold, your agent can decide to alert you or log the result.

Yes, the framework detects failures in the tool call and can automatically retry based on your configuration. It handles the network side so your agent stays focused.

We enforce strict sandbox boundaries for every request. No other user can see the series IDs or labor data your specific agent is processing.

No, your agent's interactions with the server are private. We isolate every session to ensure your research stays confidential.

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