Can I see which invoices are still unpaid?

Yes! Use the `list_agency_invoices` tool. The agent will return all invoices, and you can ask it to filter for those with an 'Unpaid' or 'Overdue' status.

How do I check the status of a specific sales proposal?

Use the `list_sales_quotes` tool. Your agent will fetch all quotes and proposals, showing their current status (e.g., Sent, Viewed, Accepted).

Where do I find my Clientjoy API Token?

Log in to your Clientjoy account, navigate to **Settings**, and select **API**. You can generate and copy your API token from that section.

Clientjoy MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: Clientjoy
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 Tools Framework

Connect your CrewAI agents to Clientjoy through Vinkius, pass the Edge URL in the `mcps` parameter and every Clientjoy 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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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Clientjoy Specialist",
    goal="Help users interact with Clientjoy effectively",
    backstory=(
        "You are an expert at leveraging Clientjoy 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 Clientjoy "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 8 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 Clientjoy MCP Server

Connect your Clientjoy account to any AI agent and take full control of your agency operations through natural conversation. Streamline how you manage the entire lifecycle from lead capture to final invoicing natively.

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

Lead Oversight — List and retrieve details for all sales leads and their capture status natively
Contact Intelligence — Access and monitor all client contacts and relationship history flawlessly
Invoicing Logistics — List all agency invoices and monitor their payment status flawlessly
Project Management — Access and monitor all client projects and their constituent tasks securely
Sales Pipelines — List and review quotes and proposals sent to potential clients flawlessly
Profile Visibility — Access your own user profile and core workspace metadata directly within your workspace flawlessly

The Clientjoy MCP Server exposes 8 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 Clientjoy to CrewAI via MCP

Follow these steps to integrate the Clientjoy 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 8 tools from Clientjoy

Why Use CrewAI with the Clientjoy MCP Server

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

Clientjoy + CrewAI Use Cases

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

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

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

Clientjoy MCP Tools for CrewAI (8)

These 8 tools become available when you connect Clientjoy to CrewAI via MCP:

get_contact_crm_details

Get detailed information for a specific contact

get_lead_crm_details

Get detailed information for a specific lead

get_my_clientjoy_profile

Retrieve information about the authenticated workspace user

list_agency_invoices

List all invoices and their payment status

list_agency_projects

List all client projects tracked in Clientjoy

list_clientjoy_contacts

List all contacts and clients stored in the CRM

list_clientjoy_leads

List all sales leads captured in Clientjoy

list_sales_quotes

List sales quotes and proposals sent to clients

Example Prompts for Clientjoy in CrewAI

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

"List all my new leads in Clientjoy."

"Show me my unpaid invoices."

"What is the status of the 'Website Redesign' project?"

Troubleshooting Clientjoy MCP Server with CrewAI

Common issues when connecting Clientjoy 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.

Clientjoy + CrewAI FAQ

Common questions about integrating Clientjoy 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.