Clientjoy MCP Server for OpenAI Agents SDK 8 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Clientjoy through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Clientjoy Assistant",
instructions=(
"You help users interact with Clientjoy. "
"You have access to 8 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Clientjoy"
)
print(result.final_output)
asyncio.run(main())
* 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.
The OpenAI Agents SDK auto-discovers all 8 tools from Clientjoy through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Clientjoy, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP
Follow these steps to integrate the Clientjoy MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 8 tools from Clientjoy
Why Use OpenAI Agents SDK with the Clientjoy MCP Server
OpenAI Agents SDK provides unique advantages when paired with Clientjoy through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Clientjoy + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Clientjoy MCP Server delivers measurable value.
Automated workflows: build agents that query Clientjoy, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Clientjoy, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Clientjoy tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Clientjoy to resolve tickets, look up records, and update statuses without human intervention
Clientjoy MCP Tools for OpenAI Agents SDK (8)
These 8 tools become available when you connect Clientjoy to OpenAI Agents SDK 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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK
Common issues when connecting Clientjoy to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Clientjoy + OpenAI Agents SDK FAQ
Common questions about integrating Clientjoy MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Clientjoy with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
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TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Clientjoy to OpenAI Agents SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.