How do I obtain my Ezus API Key?

You can find your API Key in the Ezus settings under the 'Integrations' or 'API' section. Note that a Premium plan may be required for private API access.

Can I update existing projects using this integration?

Yes! Use the `upsert_project` tool. If you provide an existing Project ID, it will update the project; otherwise, it will create a new one.

Is it possible to list invoices to track payments?

Absolutely. The `list_invoices` and `get_invoice` tools allow you to retrieve financial records and check their current status.

Ezus MCP Server for CrewAI 12 tools — connect in under 2 minutes

Name: Ezus
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 12 Tools Framework

Connect your CrewAI agents to Ezus through Vinkius, pass the Edge URL in the `mcps` parameter and every Ezus 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

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Ezus Specialist",
    goal="Help users interact with Ezus effectively",
    backstory=(
        "You are an expert at leveraging Ezus 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 Ezus "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

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

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* 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 Ezus MCP Server

Connect your Ezus travel management account to any AI agent and take full control of your agency's workflows through natural conversation.

When paired with CrewAI, Ezus becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Ezus 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

Project Management — List, fetch, and upsert travel projects directly from the Ezus cloud
Client & Supplier CRM — Query client details and manage your network of suppliers with ease
Product Catalog — Access and inspect your travel products and packages stored in the Ezus catalog
Financial Overview — List and inspect invoices to keep track of your agency's billing and financial status
User Profiling — Retrieve the underlying credentials and profile information of your agent's API user

The Ezus MCP Server exposes 12 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 Ezus to CrewAI via MCP

Follow these steps to integrate the Ezus 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 12 tools from Ezus

Why Use CrewAI with the Ezus MCP Server

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

Ezus + CrewAI Use Cases

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

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

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

Ezus MCP Tools for CrewAI (12)

These 12 tools become available when you connect Ezus to CrewAI via MCP:

get_client

Get a specific Ezus client by ID

get_invoice

Get a specific Ezus invoice by ID

get_me

Get current Ezus user profile

get_product

Get a specific Ezus product by ID

get_project

Get a specific Ezus project by ID

get_supplier

Get a specific Ezus supplier by ID

list_clients

List all Ezus clients

list_invoices

List all Ezus invoices

list_products

List all Ezus products

list_projects

List all Ezus projects

list_suppliers

List all Ezus suppliers

upsert_project

Create or update an Ezus project

Example Prompts for Ezus in CrewAI

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

"List my recent travel projects on Ezus."

"Show me the details for client ID 12345."

"Get all products available in the catalog."

Troubleshooting Ezus MCP Server with CrewAI

Common issues when connecting Ezus 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.

Ezus + CrewAI FAQ

Common questions about integrating Ezus 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.