Can I see a preview of the card before sending it?

Yes! Use the `preview_greeting_card` tool with your message and artwork ID. Your agent will return a preview URL (usually a PDF) so you can verify everything looks perfect.

How do I find the correct artwork ID for a design?

Simply ask the agent to `list_card_artwork`. It will retrieve all the available designs from your account, including their titles and unique IDs or slugs.

Does the integration support international shipping?

Yes. When using the `place_greeting_card_order` action, you can specify the country code (e.g., 'UK', 'AU', 'US'). Cardly handles the local printing and postage automatically.

Cardly MCP Server for CrewAI 9 tools — connect in under 2 minutes

Name: Cardly
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 9 Tools Framework

Connect your CrewAI agents to Cardly through Vinkius, pass the Edge URL in the `mcps` parameter and every Cardly 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="Cardly Specialist",
    goal="Help users interact with Cardly effectively",
    backstory=(
        "You are an expert at leveraging Cardly 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 Cardly "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 9 available tools "
        "and what they can do."
    ),
)

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

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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 Cardly MCP Server

Connect your Cardly account to any AI agent and orchestrate your personalized gifting, customer appreciation, and physical mail workflows through natural conversation.

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

What you can do

Order Management — Place real orders for physical greeting cards with custom messages and designs directly from your workspace.
Design Oversight — Browse your custom artwork library and retrieve detailed metadata for individual designs.
Order Preview — Generate a watermarked PDF preview of your card to verify content and layout before sending.
Contact Coordination — Access and manage your contact lists and add new recipients to your address book.
Global Shipping — Send cards to recipients in the US, Australia, UK, and worldwide with automatic address validation.
API Verification — Verify your connection and API key status instantly using the echo tool.

The Cardly MCP Server exposes 9 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 Cardly to CrewAI via MCP

Follow these steps to integrate the Cardly 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 9 tools from Cardly

Why Use CrewAI with the Cardly MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Cardly 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 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

Cardly + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Cardly 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 Cardly, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Cardly 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 Cardly against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Cardly MCP Tools for CrewAI (9)

These 9 tools become available when you connect Cardly to CrewAI via MCP:

add_contact_to_list

Add a new contact to a specific list

find_contact

Search for a contact in a list by email

get_account_info

Retrieve core account information

get_artwork_details

Get details of a specific piece of artwork

list_card_artwork

List available greeting card designs/artwork

list_contact_lists

List all contact lists in your account

place_greeting_card_order

Place a real order for a physical greeting card

preview_greeting_card

Generate a preview of a greeting card without placing a real order

verify_api_connection

Verify connectivity and API key validity

Example Prompts for Cardly in CrewAI

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

"List all the available greeting card designs in my account."

"Preview a card with artwork art_1 and message 'Happy Birthday John!'."

"Send a thank you card to Jane Smith in Australia."

Troubleshooting Cardly MCP Server with CrewAI

Common issues when connecting Cardly 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

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

Cardly + CrewAI FAQ

Common questions about integrating Cardly 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.