Skip to content

External Integrations

ChatKcal is designed to be an "Intelligence Sink" — receiving structured data from external AI agents.

The primary ingestion mechanism is a deep link generated by an LLM.

Structure: https://chatkcal.app/log?meal_json=<JSON_String>

(Note: We prioritize readable, structured data over URL compression for now).

JSON Payload:

{
  "mealSummary": "Homemade Beef Chili",
  "emoji": "\ud83c\udf72",
  "calories": 650.5,
  "protein": 45.2,
  "carbs": 35,
  "fat": 38.5,
  "notes": "High fat estimate due to generous cheddar..."
}

Note on Compatibility: The system remains backward compatible with the legacy snake_case format (meal_summary, calories_kcal, etc.).

2. Future: MCP Support

Goal: Remove the "Copy/Paste" step entirely.

We plan to implement the Model Context Protocol (MCP) to allow local LLMs (like Claude Desktop) to connect directly to ChatKcal as a tool resource.

  • Tool: add_meal(meal_data)
  • Flow: The user talks to Claude, Claude calls the add_meal tool, and ChatKcal updates instantly.