How do I find my VineRadar API Key?

Log in to your [**VineRadar dashboard**](https://vineradar.com/account), and you will find your API Key under the 'Integrations' or 'Developer' section. Copy and paste it below.

Can the agent search for vineyards by region?

Yes. Use the `search_vineyards` tool providing the location name (e.g., 'Napa Valley' or 'Bordeaux'). Your agent will return matching vineyards instantly.

Is vintage information included?

Yes. The wine records retrieved by your agent include the vintage year and specific characteristics associated with that production cycle.

VineRadar MCP Server for CrewAI 6 tools — connect in under 2 minutes

Name: VineRadar
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 6 Tools Framework

Connect your CrewAI agents to VineRadar through the Vinkius — pass the Edge URL in the `mcps` parameter and every VineRadar tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="VineRadar Specialist",
    goal="Help users interact with VineRadar effectively",
    backstory=(
        "You are an expert at leveraging VineRadar tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in VineRadar "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 6 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About VineRadar MCP Server

Empower your AI agent to orchestrate your entire wine research and vineyard auditing workflow with VineRadar, the comprehensive platform for global wine data. By connecting VineRadar to your agent, you transform complex varietal searches into a natural conversation. Your agent can instantly search for specific wines, audit vineyard locations, and retrieve detailed vintage metadata without you ever touching a wine app. Whether you are building a personal cellar or conducting market research on varietals, your agent acts as a real-time sommelier, ensuring your data is always detailed and well-categorized.

When paired with CrewAI, VineRadar becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call VineRadar tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

What you can do

Wine Auditing — Search for thousands of wines by name or keyword and retrieve detailed metadata, including ratings and vintages.
Vineyard Oversight — Browse vineyard profiles by location to maintain a clear view of regional wine production.
Varietal Discovery — Query wine varietals to understand the technological and regional distribution of specific grape types instantly.
Vintage Intelligence — Retrieve full details for specific wine IDs to assist in deep-dive collection audits.
Market Monitoring — List all supported varietals in the VineRadar catalog to identify trending wine themes in real-time.

The VineRadar MCP Server exposes 6 tools through the Vinkius. Connect it to CrewAI 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 VineRadar to CrewAI via MCP

Follow these steps to integrate the VineRadar MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 6 tools from VineRadar

Why Use CrewAI with the VineRadar MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with VineRadar through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

VineRadar + CrewAI Use Cases

Practical scenarios where CrewAI combined with the VineRadar MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries VineRadar for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries VineRadar, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain VineRadar tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries VineRadar against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

VineRadar MCP Tools for CrewAI (6)

These 6 tools become available when you connect VineRadar to CrewAI via MCP:

check_api_status

Check if the VineRadar API is operational

get_vineyard_details

Get full details for a specific vineyard by ID

get_wine_details

Get full details for a specific wine by ID

list_wine_varietals

List all wine varietals supported by VineRadar

search_vineyards

Search for vineyards by location

search_wines

Search for wines by name or keyword

Example Prompts for VineRadar in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with VineRadar immediately.

"Search for 'Cabernet Sauvignon' wines using VineRadar."

"Find vineyards in 'Napa Valley'."

"What are the details for wine ID 12345?"

Troubleshooting VineRadar MCP Server with CrewAI

Common issues when connecting VineRadar to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

VineRadar + CrewAI FAQ

Common questions about integrating VineRadar MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.