How to Use the Cliengo MCP in OpenAI Agents SDK

Q: How do I connect Cliengo to the OpenAI Agents SDK?

Initialize your MCP environment by setting up MCPServerStreamableHttp pointing to your Vinkius endpoint. Pass this server instance inside the mcpservers list when initializing your agent.

Q: Can my OpenAI Agents SDK setup handle high-volume Cliengo lead lists?

Yes, by passing cacheToolsList=True inside your python configuration. This prevents the agent from making redundant discovery calls when querying listcliengoleads repeatedly.

Q: How does OpenAI Agents SDK manage multi-agent handoffs for Cliengo chats?

Your primary coordinator agent uses listchatconversations to evaluate active threads. It then hands off specific conversations to specialized support or sales agents based on the chat text.

Q: Can I register webhooks for Cliengo using this setup?

You run listcliengowebhooks to inspect existing endpoints. Your agent can then verify if real-time lead events are properly routing to your backend systems.

Feed Cliengo lead data and chat history directly to your OpenAI Agents SDK workflow with zero manual data mapping.

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Connect Cliengo MCP to OpenAI Agents SDK

Create your Vinkius account to connect Cliengo to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Cliengo with OpenAI Agents SDK

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Audit Cliengo chat logs using OpenAI Agents SDK

`get_chat_history` pulls raw message logs from your chatbot conversations straight into your run loop. Your agent parses the text to find unanswered customer questions or friction points in your funnel. By loading this history, the OpenAI Agents SDK routes the user state to specialized agents. You get clear tracing in your dashboard showing exactly how the agent evaluated the conversation before deciding on the next action.

Feed lead details into OpenAI Agents SDK guardrails

`get_lead_details` extracts contact information and custom fields captured by your website chatbot. This tool exposes the raw customer record so your python agent can inspect the payload immediately. The OpenAI Agents SDK runs validation checks on these lead properties before triggering downstream updates. If a phone number or email format looks corrupt, the system halts execution before bad data pollutes your CRM.

Automate website lead routing via the MCP Server

`list_cliengo_websites` maps out every active domain where your chat widget is currently capturing visitors. This MCP tool gives your agent the layout of your entire digital footprint in one quick query. Using this mapping, your OpenAI Agents SDK setup distributes incoming chat leads to the correct regional sales agents. You avoid manual routing mistakes because the agent cross-references active sites with your internal directory.

Setup guide

Set up Cliengo MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Cliengo tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Cliengo tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Cliengo tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Cliengo Agent",
            instructions="You have access to Cliengo tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Cliengo. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Cliengo MCP in OpenAI Agents SDK

Initialize your MCP environment by setting up `MCPServerStreamableHttp` pointing to your Vinkius endpoint. Pass this server instance inside the `mcp_servers` list when initializing your agent.

Yes, by passing `cacheToolsList=True` inside your python configuration. This prevents the agent from making redundant discovery calls when querying `list_cliengo_leads` repeatedly.

Your primary coordinator agent uses `list_chat_conversations` to evaluate active threads. It then hands off specific conversations to specialized support or sales agents based on the chat text.

You run `list_cliengo_webhooks` to inspect existing endpoints. Your agent can then verify if real-time lead events are properly routing to your backend systems.

Your chat history and lead details remain isolated within a secure V8 sandbox. Vinkius handles the authorization token securely, meaning your OpenAI client never exposes raw API credentials to external logs.

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