How to Use the BLS Wages — OEWS Occupational Employment MCP in VS Code Copilot

Equip your VS Code Copilot team with real-time BLS wage and occupational data.

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Connect BLS Wages — OEWS Occupational Employment MCP to VS Code Copilot

Create your Vinkius account to connect BLS Wages — OEWS Occupational Employment to VS Code Copilot 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 Wages — OEWS Occupational Employment with VS Code Copilot

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Enable team-wide wage queries via VS Code Copilot

The `query_bls` tool lets your entire development team pull official occupational wage data directly through shared workspace configs. By committing the MCP configuration to your repository, every engineer instantly gains access to the same data sources. This team-wide setup ensures consistency across your development environments. No one has to manually configure individual API keys or local database mirrors.

Pull up to 50 concurrent wage series

The `query_bls` tool handles 50 parallel lookbacks to fetch complex occupational employment statistics in a single call. Your agent can build detailed wage comparisons across multiple states without stalling. The raw JSON output is formatted instantly for consumption by your local services. This speeds up the testing of data pipelines and reporting modules.

Query raw government data without external wrappers

The `query_bls` tool connects your agent directly to the BLS v2 API database via this MCP Server. You don't need to maintain third-party npm packages or custom python wrappers that break when government endpoints update. This direct connection keeps your codebase clean and lightweight. Your agent handles the raw payload formatting, translating numeric codes into readable data structures.

Setup guide

Set up BLS Wages — OEWS Occupational Employment MCP in VS Code Copilot

Prerequisites

VS Code 1.99 or later with GitHub Copilot extension
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and run "MCP: Add Server". Select HTTP (Streamable) as the server type. VS Code will create .vscode/mcp.json in your workspace.
2

Add the BLS Wages — OEWS Occupational Employment MCP

Paste the JSON snippet shown on the right into your .vscode/mcp.json. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Switch to Agent mode

Open Copilot Chat (Cmd+Shift+I / Ctrl+Shift+I) and switch to Agent mode using the dropdown. MCP tools are only available in Agent mode — they do not appear in Edit or Ask modes.
4

Verify the connection

In the Copilot Chat input, type # to list available tools. You should see the BLS Wages — OEWS Occupational Employment tools listed. Try asking: "List my recent BLS Wages — OEWS Occupational Employment transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

{
  "mcpServers": {
    "bls-wages-oews-occupational-employment-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about BLS Wages — OEWS Occupational Employment MCP in VS Code Copilot

Create a .vscode/mcp.json file in your repository root and add the server configuration. When team members open the project in VS Code 1.96+, Copilot will automatically detect and load the MCP tools.

Yes, the server supports up to 50 concurrent lookbacks per request. Copilot can execute these parallel queries to fetch historical wage trends across several job categories at once.

You must provide valid BLS Series IDs associated with the Occupational Employment and Wage Statistics survey. The server uses these specific identifiers to pull the correct median earnings data.

This specific setup guide is for VS Code Copilot, but the underlying MCP server works with any compatible client, including Cursor and Claude Desktop.

All wage queries and BLS Series IDs are processed through an encrypted, ephemeral MCP sandbox. The transmission is fully sandboxed, ensuring your sensitive HR research and query parameters are never stored.

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