How do I find my ReciPal API Key?

Log in to your [**ReciPal account**](https://recipal.com/), navigate to your account settings, and you will find your API Key in the integrations or developer section. Copy and paste it below.

Can the agent show serving sizes?

Yes. Every recipe record retrieved by your agent includes serving size metadata and the number of servings per recipe.

Does it support ingredient lists?

Yes. The `get_recipe_details` tool retrieves the full list of ingredients used in a specific recipe, along with their weights.

ReciPal MCP Server for LangChain 4 tools — connect in under 2 minutes

Name: ReciPal
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 4 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect ReciPal through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "recipal": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using ReciPal, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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About ReciPal MCP Server

Empower your AI agent to orchestrate your entire food manufacturing and recipe auditing workflow with ReciPal, the specialized source for nutritional labeling data. By connecting ReciPal to your agent, you transform complex ingredient analysis into a natural conversation. Your agent can instantly retrieve recipe details, audit calorie counts, and query ingredient lists without you ever touching a labeling portal. Whether you are conducting product research or managing regional dietary constraints, your agent acts as a real-time nutritional consultant, ensuring your data is always verified and precise.

LangChain's ecosystem of 500+ components combines seamlessly with ReciPal through native MCP adapters. Connect 4 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Recipe Auditing — Retrieve high-resolution details for all recipes in your catalog, including names, calorie counts, and serving metadata.
Ingredient Oversight — Audit the available ingredients in the ReciPal database to understand the thematic distribution of components instantly.
Nutritional Intelligence — Query full nutritional breakdowns for specific recipes to assist in deep-dive dietary classification.
Resource Discovery — Retrieve unique recipe identifiers to help you identify relevant markers for your food products.
Operational Monitoring — Check API status to ensure your nutritional research workflow is always operational.

The ReciPal MCP Server exposes 4 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect ReciPal to LangChain via MCP

Follow these steps to integrate the ReciPal MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 4 tools from ReciPal via MCP

Why Use LangChain with the ReciPal MCP Server

LangChain provides unique advantages when paired with ReciPal through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine ReciPal MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across ReciPal queries for multi-turn workflows

ReciPal + LangChain Use Cases

Practical scenarios where LangChain combined with the ReciPal MCP Server delivers measurable value.

RAG with live data: combine ReciPal tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query ReciPal, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain ReciPal tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every ReciPal tool call, measure latency, and optimize your agent's performance

ReciPal MCP Tools for LangChain (4)

These 4 tools become available when you connect ReciPal to LangChain via MCP:

check_api_status

Check if the ReciPal service is operational

get_recipe_details

Get full nutritional and ingredient details for a specific recipe by ID

list_recipal_ingredients

List all ingredients available in the ReciPal database

list_recipal_recipes

List all recipes in your ReciPal account

Example Prompts for ReciPal in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with ReciPal immediately.

"List all my recipes using ReciPal."

"What are the details for recipe ID '12345'?"

"List all ingredients available in ReciPal."

Troubleshooting ReciPal MCP Server with LangChain

Common issues when connecting ReciPal to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

ReciPal + LangChain FAQ

Common questions about integrating ReciPal MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.