How to Use the BLS Wages — OEWS Occupational Employment MCP in Mastra AI
Build automated HR workflows with Mastra AI and live BLS wage statistics.
Works with every AI agent you already use
…and any MCP-compatible client
Connect BLS Wages — OEWS Occupational Employment MCP to Mastra AI
Create your Vinkius account to connect BLS Wages — OEWS Occupational Employment 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.
Build resilient wage workflows with Mastra AI
Running the `query_bls` tool inside a Mastra AI workflow ensures your occupational wage lookups never fail silently due to rate limits. Government APIs are finicky, but this MCP server integration lets you configure automatic retries with exponential backoff. If a series lookup fails, the agent pauses, backs off, and tries again without crashing your entire pipeline. Your automated payroll or recruiting tools keep running smoothly in the background.
Human-in-the-loop validation for HR data
Protect sensitive salary queries by wrapping the `query_bls` tool in Mastra's `requireToolApproval` step. Using Mastra's approval gate in this MCP integration is a lifesaver when dealing with critical HR decisions. This keeps a human supervisor in control of salary choices while letting the agent do the heavy lifting of pulling raw stats.
Conditional branching based on median earnings
Branch your workflow logic dynamically based on the salary data returned by the `query_bls` tool. Mastra's workflow engine lets you build complex conditional statements around your wage queries. If the agent finds that a state's median wage exceeds a certain threshold, it can automatically branch to run different analysis tools. This lets you build fully autonomous recruiting pipelines that adjust offer ranges on the fly.
Set up BLS Wages — OEWS Occupational Employment MCP in Mastra AI
Prerequisites
- Node.js 18+ and a TypeScript project
-
@mastra/mcp+@mastra/corepackages - Active Vinkius subscription with a valid endpoint token
- 1
Install dependencies
Run
npm install @mastra/mcp @mastra/coreplus your preferred model provider (e.g.@ai-sdk/openai). - 2
Configure the MCPClient
Create an
MCPClientwith your Vinkius endpoint as aURLobject. 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'stoolsobject. All BLS Wages — OEWS Occupational Employment tools become native Mastra tools. - 4
Run with any model
Swap
openai("gpt-4o")for any AI SDK-compatible provider. Callagent.generate()and the agent routes tool calls through MCP automatically.
import { MCPClient } from "@mastra/mcp";
import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
const mcpClient = new MCPClient({
id: "bls-wages-oews-occupational-employment-mcp-client",
servers: {
"bls-wages-oews-occupational-employment-mcp": {
url: new URL(
"https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
),
},
},
});
const agent = new Agent({
name: "BLS Wages — OEWS Occupational Employment Agent",
model: openai("gpt-4o"),
instructions: "You have access to BLS Wages — OEWS Occupational Employment tools.",
tools: {
...(await mcpClient.listTools()),
},
});
const result = await agent.generate(
"List recent BLS Wages — OEWS Occupational Employment transactions"
);
console.log(result.text); Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Bureau of Labor Statistics. 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 BLS Wages — OEWS Occupational Employment MCP in Mastra AI
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