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recipes

by io.github.pipeworx-io

Get Meal

get_meal
Read-onlyIdempotent

Get complete recipe details including ingredients with measurements and step-by-step cooking instructions. Pass a meal ID from search_meals or random_meal.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesTheMealDB meal ID (e.g., "52772")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesTheMealDB meal ID
areaYesCuisine area/region (e.g., Italian, Indian)
nameYesMeal name
tagsYesList of meal tags/keywords
categoryYesMeal category (e.g., dessert, seafood)
source_urlYesSource website URL
ingredientsYesList of ingredients with measurements
youtube_urlYesYouTube video URL for recipe
instructionsYesStep-by-step cooking instructions
thumbnail_urlYesURL to meal thumbnail image

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "area": {
+      "description": "Cuisine area/region (e.g., Italian, Indian)",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "category": {
+      "description": "Meal category (e.g., dessert, seafood)",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "id": {
+      "description": "TheMealDB meal ID",
+      "type": "string"
+    },
+    "ingredients": {
+      "description": "List of ingredients with measurements",
+      "items": {
+        "properties": {
+          "ingredient": {
+            "description": "Ingredient name",
+            "type": "string"
+          },
+          "measure": {
+            "description": "Measurement quantity and unit",
+            "type": "string"
+          }
+        },
+        "required": [
+          "ingredient",
+          "measure"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "instructions": {
+      "description": "Step-by-step cooking instructions",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "name": {
+      "description": "Meal name",
+      "type": "string"
+    },
+    "source_url": {
+      "description": "Source website URL",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "tags": {
+      "description": "List of meal tags/keywords",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "thumbnail_url": {
+      "description": "URL to meal thumbnail image",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "youtube_url": {
+      "description": "YouTube video URL for recipe",
+      "type": [
+        "string",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "id",
+    "name",
+    "category",
+    "area",
+    "instructions",
+    "thumbnail_url",
+    "youtube_url",
+    "source_url",
+    "tags",
+    "ingredients"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "id": "52772"
+  },
+  {
+    "id": "52804"
+  }
+]
  3. First observed

TDQS

A4.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is established. The description adds no further behavioral caveats (e.g., errors, rate limits) but also doesn't contradict annotations. It adds minimal extra context beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core action, and contains no filler. Every sentence earns its place, covering what it returns and how to construct the call.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (single required parameter), the existing output schema, and comprehensive annotations, the description is sufficiently complete. It tells the agent what the tool does, what the output includes, and where to source the ID, covering all necessary selection and invocation context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already documents the 'id' parameter with examples and description (100% coverage), so the baseline is 3. The description adds valuable semantic context by telling the agent where to obtain valid IDs ('from search_meals or random_meal'), which helps ensure correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get complete recipe details' with specific content (ingredients, measurements, step-by-step instructions). It distinguishes from siblings like search_meals (which lists meals) and random_meal (which returns a random meal) by specifying this tool retrieves full details for a given ID.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says 'Pass a meal ID from search_meals or random_meal', giving a clear workflow for when to use this tool. It doesn't explicitly mention alternatives to avoid, but the context makes it obvious this is the detail-fetching step after obtaining an ID.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4/5.0
Disambiguation5/5

Each tool has a highly specific purpose with detailed descriptions, making them easily distinguishable. Overlaps are minimal; for instance, Pipeworx and Polymarket tools have distinct roles within their domains.

Naming Consistency4/5

Most tools follow a consistent snake_case pattern (e.g., ask_pipeworx, compare_entities), but a few single-word names (e.g., forget, recall) deviate slightly, causing minor inconsistency.

Tool Count2/5

The server is named 'recipes' but contains only 4 recipe-related tools out of 34. The majority cover unrelated domains like finance, betting, and data queries, making the scope overly broad and misaligned with the server name.

Completeness2/5

For the 'recipes' domain, essential CRUD operations and features like meal planning are missing. While the general tool set is extensive, it lacks critical recipe-related functionality, leaving significant gaps for the intended purpose.

Resources