> ## Documentation Index
> Fetch the complete documentation index at: https://docs.enginy.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Connect VS Code

> Register the hosted Enginy MCP server in VS Code and GitHub Copilot Agent mode via mcp.json.

## Before you start

This path is best suited to teams already using a VS Code MCP workflow, including GitHub Copilot Agent mode
and other VS Code-based clients that support remote MCP from project configuration.

An Enginy admin just needs to enable the MCP integration for the workspace — that's it to get started. Enginy
grants full access by default; restricting policy scopes is an optional, advanced step for later.

## Add the hosted server

Add Enginy to `.vscode/mcp.json`:

```json theme={null}
{
  "servers": {
    "enginy": {
      "type": "http",
      "url": "https://openapi.enginy.ai/mcp"
    }
  }
}
```

Reload the MCP servers in VS Code and let it open the browser flow to approve Enginy.

## Verify the connection

After authorization, ask the assistant to use Enginy MCP and run:

```text theme={null}
mcp_whoami
```

That confirms the hosted MCP server is reachable, OAuth completed, and the granted scopes match what Enginy approved.

<CardGroup cols={2}>
  <Card title="Client support matrix" icon="table-list" href="/mcp/client-support-matrix">
    Compare support levels and setup shapes across every Enginy MCP client.
  </Card>

  <Card title="Security and troubleshooting" icon="triangle-exclamation" href="/mcp/security-troubleshooting">
    Debug auth, scope, token, and transport issues after VS Code connects.
  </Card>
</CardGroup>