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

# Continue

> Connect Continue to Dreamtune MCP and install scoped workflow skills.

<img src="https://mintcdn.com/dreamtune/alDlJCy5wJhi5BBd/images/agents/continue.png?fit=max&auto=format&n=alDlJCy5wJhi5BBd&q=85&s=8f9e96fb07fbef897a8ef70efd12f873" alt="Continue official logo" width="48" height="48" data-path="images/agents/continue.png" />

## Before you connect

Create a Dreamtune workspace API key with only the permissions you need.
Hosted HTTP setup needs no Dreamtune package installation. Local stdio setup
requires Node.js 22.20 or later and the published CLI.

## Configure

Merge this server entry into .continue/mcpServers/dreamtune.yaml. Preserve any other servers or settings.

```yaml theme={null}
name: Dreamtune
version: 1.0.0
schema: v1
mcpServers:
  - name: Dreamtune
    type: stdio
    command: dreamtune
    args: [mcp]
    env:
      DREAMTUNE_API_KEY: ${{ secrets.DREAMTUNE_API_KEY }}
      DREAMTUNE_API_ORIGIN: https://dreamtune-api.fly.dev
      DREAMTUNE_REQUEST_TIMEOUT_MS: "135000"
```

Install @dreamtune/sdk globally, then supply DREAMTUNE\_API\_KEY through Continue's secrets configuration. Keep name, version and schema in the standalone file. This guide uses the documented local stdio form. Restart the agent after changing server settings.

## Verify the connection

Restart the client after changing settings or its environment. Open its MCP
server/tool status view and check that Dreamtune tools are listed. Ask it:

> Use Dreamtune to read model request limits. Do not execute a model, tool or GPU.

Confirm model\_limits returns limits before authorizing paid work. Then inspect a
catalog schema and use one explicitly approved operation. Keep client approval
controls enabled. Never put the key in a chat message, URL or repository.

## Add workflow instructions

Install the [Dreamtune skills](/connect/skills-install) into the skills directory
supported by your client, or copy the platform skill into a user instruction
workflow. A skill guides the agent; MCP provides execution. Neither grants extra
key permissions. See [troubleshooting](/errors) for 401, missing scopes, timeouts
and key/environment problems.

Configuration verified against [the official client documentation](https://docs.continue.dev/customize/deep-dives/mcp).


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