How to Use the Umami Cloud MCP in OpenAI Agents SDK

Get accurate web metrics and user counts in your production agent system using the OpenAI Agents SDK.

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Connect Umami Cloud MCP to OpenAI Agents SDK

Create your Vinkius account to connect Umami Cloud 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 Umami Cloud with OpenAI Agents SDK

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Fetch detailed website traffic data with Umami Cloud MCP Server.

When you run the `websites` tool, your agent gets specific details like URLs, browsers, OS, and devices for any given site. This structured output allows subsequent steps in your workflow to build highly accurate profiles of user activity. The guardrails in the OpenAI Agents SDK validate this data before execution. You won't get corrupted fields; you’ll know exactly what metrics the agent pulled from Umami Cloud.

Manage multi-step web analysis flows with OpenAI Agents SDK.

Your production agents can pass off tasks seamlessly, like running `websites` and then feeding that data to a specialized reporting agent. The built-in tracing lets you see exactly which metrics were pulled and how the system processed them. This capability means your multi-agent workflows are auditable, ensuring every step using Umami Cloud MCP Server adheres to safety constraints.

Quickly determine active user counts with Umami Cloud.

Call the `users` tool to pull a simple count of how many people are actively visiting your website. This gives you immediate, clean data points perfect for performance dashboards. Because this operation is fully typed and managed by the SDK, you get reliable integers every time you check active user counts.

Setup guide

Set up Umami Cloud 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 Umami Cloud tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Umami Cloud 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="Umami Cloud Agent",
            instructions="You have access to Umami Cloud tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Umami Cloud MCP in OpenAI Agents SDK

You pass the MCP Server object directly to your Agent constructor. Because the OpenAI Agents SDK auto-discovers tools, you don't need manual configuration for `users` or `websites`. It just works.

Absolutely. The OpenAI Agents SDK is designed for deployed products. You can integrate the MCP Server into your main operational flow, leveraging its built-in guardrails to keep everything safe.

The server touches web analytics data, specifically user counts and website metrics (URLs, browsers, OS, devices). The OpenAI Agents SDK handles this data within its validated context.

Yes. You can chain operations—for instance, get site metrics via `websites`, and then use those results to calculate an aggregate count using `users`.

It is. The combination of Umami Cloud's focused analytics data and the OpenAI Agents SDK's validation layer means you're building something robust, not just a proof-of-concept.

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