How to Use the Spoonacular MCP in Google ADK

Q: Can the Google ADK handle complex meal planning with Spoonacular Alternative?

Yes. You can chain tools—first using recipesbyingredients to narrow options, then running analyzerecipe on the top candidates for deeper data enrichment.

Q: Does the MCP Server support importing recipes?

The extractrecipe tool lets your agent scrape and ingest structured recipe data from external URLs. It keeps your enterprise records clean.

Q: If I use Spoonacular Alternative with Google ADK, how do I get detailed instructions?

Use the getrecipeinstructions tool. This provides clear, step-by-step analysis for a recipe ID, which is useful when generating operational procedures within your cloud environment.

Connect food data and meal logic using the Google ADK.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Spoonacular MCP to Google ADK

Create your Vinkius account to connect Spoonacular to Google ADK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Spoonacular with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Manage recipes with the MCP Server.

The `get_recipe_info` tool pulls comprehensive details about a single recipe. If you need to process many records, use `get_recipes_bulk`. This makes it easy to ingest large sets of raw recipe data into BigQuery. Need basic search metadata? The `search_recipes` function returns title, ready time, and serving sizes immediately.

Plan meals based on available ingredients.

`recipes_by_ingredients` is key for enterprise meal planning. You define the inventory (the ingredients), and it returns recipes ranked by how many items you actually have in stock. For inspiration, `random_recipes` offers suggestions that can optionally be filtered by tags, giving your models diverse data sets to work with.

Determine nutritional requirements.

`recipes_by_nutrients` lets you filter recipes against specific dietary mandates. This is perfect for feeding structured health data into Vertex AI. Plus, `get_recipe_nutrition` provides the exact metrics (like fat or sodium) needed to validate records before committing them to your enterprise data lake.

Setup guide

Set up Spoonacular MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Spoonacular tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Spoonacular_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Spoonacular tools via MCP.",
    tools=mcp_tools,
)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Spoonacular. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Spoonacular now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Spoonacular MCP in Google ADK

You pass the MCP Server endpoint to LlmAgent. Your agents can then use tools like `search_recipes` or `get_recipe_nutrition` to enrich data sets that already live in BigQuery.

This server manages structured food and nutritional data, including ingredient lists, nutrient profiles (`get_recipe_nutrition`), and recipe metadata from `search_recipes`.

Yes. You can chain tools—first using `recipes_by_ingredients` to narrow options, then running `analyze_recipe` on the top candidates for deeper data enrichment.

The `extract_recipe` tool lets your agent scrape and ingest structured recipe data from external URLs. It keeps your enterprise records clean.

Use the `get_recipe_instructions` tool. This provides clear, step-by-step analysis for a recipe ID, which is useful when generating operational procedures within your cloud environment.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript