A Public API and/or MCP Server Integration

I am currently building an AI-assisted meal planning workflow using Claude (Anthropic) to automate weekly menu generation, shopping lists, and calorie tracking. The workflow is technically complete — except for one critical gap: Yazio has no public API, which means Claude cannot read my favourite dishes, retrieve my nutrition targets, or log meals directly into my diary.
Specifically, I am requesting:
1. Read access via API — ability to retrieve saved/favourite foods and meals, personal nutrition targets, and macro profiles per user
2. Write access via API — ability to log food diary entries (meals, portions, dates) programmatically on behalf of the authenticated user
3. MCP server support — publishing a Yazio MCP (Model Context Protocol) server would allow native integration with AI assistants like Claude, enabling a new class of intelligent nutrition workflows without requiring Yazio to build AI features in-house

The Use Case
Every Friday, I want an AI assistant to:
• Pull my favourite dishes from Yazio
• Generate a calorie-matched weekly menu for two people
• Output a shopping list optimised to minimise ingredient waste
• Automatically log the accepted meal plan into both of our Yazio diaries with correct portions
This is not a niche request. As AI assistants become mainstream productivity tools, the gap between apps with API access and those without will increasingly drive user decisions. Yazio’s competitors who open their data layer first will capture the technically sophisticated health-conscious user segment.
What Already Works
Yazio’s CSV export (Pro feature) is a partial workaround for historical data, but it does not solve real-time read/write integration needs or future planning based on the recipes data base.