Engine Configuration

Engine config is the core persona and strategy file that powers all AI generation. Every brief and every content generation prompt draws from this configuration.

What is in engine config?

Engine config stores:

• Workspace name -- Used in MCP responses and UI labels
• Product description -- Grounding context injected into all generation prompts
• Brand voice -- Tone, style, and language preferences
• Channels -- Which platforms you distribute content on
• Audiences -- Segments you write for, with platform affinities
• Content pillars -- Recurring topic themes (optional)
• Competitor context -- Positioning notes (optional)

Editing engine config

Go to Settings > Engine Config or call the get_engine_config and update_channel MCP tools.

All fields are optional but more detail produces better content. A strong product description and clear audience definitions are the highest-leverage inputs.

Channels

Each channel in your config has settings specific to that platform:

Channel	Key settings
X	Max character count, preferred hashtag strategy
LinkedIn	Article vs. post preference, target connection type
Blog	Default content length, internal link strategy
Newsletter	Issue format (long-form vs. digest), send cadence
Discord	Server and channel target, tone (casual vs. formal)
YouTube	Script vs. outline, description format
Instagram	Caption style, hashtag density
Reddit	Subreddit targets, link post vs. text post

Audiences

You can define up to four audience segments. Each segment includes a name, a description of what they care about, and which platforms they prefer. The AI uses audience data to adjust framing, vocabulary, and calls to action.

Example audiences:

• Primary: Founders building B2B SaaS products -- care about growth, churn, positioning
• Secondary: Heads of marketing at Series A companies -- care about attribution, pipeline
• Niche: Developer advocates -- care about technical depth, code examples, credibility

Reference documents

Upload documents that give the AI additional context. Good candidates:

• Product spec or feature list
• Past high-performing blog posts
• Brand voice and style guide
• Messaging framework or positioning deck
• Customer research or FAQ

Documents are retrieved via semantic search during generation. The AI references the most relevant sections based on the brief topic.

Updating config via MCP

{
  "tool": "update_channel",
  "arguments": {
    "platform": "linkedin",
    "enabled": true,
    "voiceNotes": "Professional but direct. No buzzwords. Lead with the insight."
  }
}

The update_channel tool's exact arguments are described by its input schema, which your MCP client reads directly. See the MCP overview for how the self-describing server works.