How to Use the Matomo Alternative MCP in OpenAI Agents SDK

Q: Does this work with the WordPress plugin for Matomo?

It does. The getwpprocessedreport tool is specifically designed to pull reports from a Matomo instance that's managed via the official WordPress plugin.

Build analytics agents that don't fail in production. Connect the OpenAI Agents SDK to your self-hosted Matomo instance.

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Connect Matomo Alternative MCP to OpenAI Agents SDK

Create your Vinkius account to connect Matomo Alternative 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 Matomo Alternative with OpenAI Agents SDK

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Track User Behavior Safely

Your agent can log every page view, custom event, or conversion without direct database access. Use `track_action` for individual events or `track_bulk` to send a batch of user interactions at once. The OpenAI SDK's built-in guardrails mean you can let your agent track activity, knowing it can't execute an invalid action. This isn't just about sending data; it's about building a reliable system. Your agent can decide when to batch events to reduce server load, and you get full tracing in the OpenAI dashboard to see exactly what it tracked and why. It's the right way to build analytics into a production agent.

Pull Reports and Metrics for your OpenAI Agent

Get analytics data back into your agent's context. Ask it to `get_visits_summary` for top-line numbers like total visits and bounce rates. The agent gets structured data it can reason about, not just a webpage it has to scrape. For more detail, have the agent call `get_processed_report`. It returns a full, human-readable report that you can pass between specialized agents. One agent could fetch the data, and another could summarize it for a daily Slack update. This MCP Server makes that handoff possible.

Generate Charts on Demand

Sometimes numbers aren't enough. You need a chart. Your agent can call `get_image_graph` to generate a PNG of your site's traffic over a specific period. This is great for building internal dashboards or automated reports. The agent doesn't just describe the data; it shows you. You get back raw image data, ready to be embedded in an email, a web page, or saved to a file.

Setup guide

Set up Matomo Alternative 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 Matomo Alternative tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Matomo Alternative 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="Matomo Alternative Agent",
            instructions="You have access to Matomo Alternative 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 Matomo Alternative MCP in OpenAI Agents SDK

You connect the server to your agent as a toolset. The OpenAI Agents SDK automatically discovers all the analytics tools like `track_action` and `get_visits_summary`, making them available for your agent to call based on user requests or its own logic.

It's about safety and context. The MCP standard and the OpenAI SDK's guardrails prevent your agent from making malformed requests. Plus, the agent understands the tools' capabilities, so it can chain commands like fetching a report and then summarizing it.

Yes, that's a primary use case. Your agent can expose an endpoint that your web app calls. The agent then uses the `track_action` or `track_bulk` tools from this server to securely log the event in your Matomo instance.

It does. The `get_wp_processed_report` tool is specifically designed to pull reports from a Matomo instance that's managed via the official WordPress plugin.

Your data stays between your agent and your self-hosted Matomo instance. This MCP server runs in a Vinkius sandboxed environment and only proxies requests. It doesn't store any of your visitor behavior data, tracking events, or report contents.

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