Zengain MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 10 tools to Get Analytics Summary, Get Health Score, Get Product, and more
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Zengain through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
Ask AI about this App Connector for OpenAI Agents SDK
The Zengain app connector for OpenAI Agents SDK is a standout in the Data Analytics category — giving your AI agent 10 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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="Zengain Assistant",
instructions=(
"You help users interact with Zengain. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Zengain"
)
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 Zengain MCP Server
Connect your Zengain (Nalpeiron Growth Platform) account to any AI agent and simplify your customer success and usage analytics workflows through natural conversation.
The OpenAI Agents SDK auto-discovers all 10 tools from Zengain through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Zengain, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Product Lifecycle — List all registered products and retrieve detailed configuration metadata
- User Engagement — Query product users, inspect their profiles, and calculate real-time health scores
- Usage Analytics — Get high-level analytics summaries and track custom events to monitor feature adoption
- KPM Tracking — Monitor Key Product Milestones to identify successful onboarding and churn risks
- System Monitoring — List configured webhooks to understand your integration data flow
The Zengain MCP Server exposes 10 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.
All 10 Zengain tools available for OpenAI Agents SDK
When OpenAI Agents SDK connects to Zengain through Vinkius, your AI agent gets direct access to every tool listed below — spanning customer-success, product-analytics, lead-scoring, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Get analytics summary
Get customer health score
Get details for a specific product
Get details for a specific user
List tracking events
List Key Product Milestones
List Zengain products
List product users
List configured webhooks
Track a custom event
Connect Zengain to OpenAI Agents SDK via MCP
Follow these steps to wire Zengain into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install the SDK
pip install openai-agents in your Python environmentReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comRun the script
python agent.pyExplore tools
Why Use OpenAI Agents SDK with the Zengain MCP Server
OpenAI Agents SDK provides unique advantages when paired with Zengain 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
Zengain + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Zengain MCP Server delivers measurable value.
Automated workflows: build agents that query Zengain, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Zengain, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Zengain tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Zengain to resolve tickets, look up records, and update statuses without human intervention
Example Prompts for Zengain in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Zengain immediately.
"List all products in my Zengain account."
"What is the health score for user 'customer_456'?"
"Show me a summary of usage analytics for this month."
Troubleshooting Zengain MCP Server with OpenAI Agents SDK
Common issues when connecting Zengain to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Zengain + OpenAI Agents SDK FAQ
Common questions about integrating Zengain 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.