Schema | Tandoor MCP Server

Tandoor MCP Server

Describes the environment variables required to run the server.

Name	Required	Description	Default
`TANDOOR_URL`	Yes	The URL of your Tandoor instance
`TANDOOR_TOKEN`	Yes	Your Tandoor API token (Get from Settings → API Tokens → Create new token)

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{}

Functions exposed to the LLM to take actions

Name	Description
list_recipesC	List recipes with optional filters: page, page_size, query, sort_order, rating_gte
get_recipeC	Get recipe details by ID
create_recipeC	Create recipe. Required: name, steps[{instruction, ingredients[{food, amount, unit?}]}]. Optional: description, servings, working_time, waiting_time, keywords[]
update_recipeB	Update recipe metadata and content. Only provide fields you want to update. All fields optional except id.
list_meal_plansC	List meal plans. Optional: from_date, to_date (YYYY-MM-DD), page, page_size
get_meal_planC	Get meal plan by ID
create_meal_planC	Create meal plan. Required: from_date (ISO), meal_type_id, servings. Optional: recipe_id, title, note, addshopping
update_meal_planC	Update meal plan. Required: id. All other fields optional
delete_meal_planC	Delete meal plan by ID
auto_meal_planC	Auto-generate meal plans. Required: start_date, end_date (YYYY-MM-DD), meal_type_id, keyword_ids[], servings, addshopping
list_meal_typesB	List available meal types (breakfast, lunch, dinner, etc.)

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

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curl -X GET 'https://glama.ai/api/mcp/v1/servers/mc-mario/tandoor-mcp'

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