How to Use the Matomo Alternative MCP in LangChain

Q: How do I connect the Matomo Alternative MCP Server to LangChain?

Install the adapter with pip install langchain-mcp-adapters. Then, instantiate MultiServerMCPClient with your Vinkius endpoint URL, call .gettools(), and pass the resulting list to your agent factory.

Q: Can my LangChain agent use Matomo Alternative to build a daily email report?

Yes. A common chain is to call getvisitssummary, format the numbers into a string, and then pass that string to an email or Slack tool. The agent orchestrates the whole sequence.

Q: When should my LangChain agent use trackbulk vs trackaction with Matomo Alternative?

Use trackaction for critical, real-time events like a purchase. Use trackbulk for less critical actions or high-volume logging to reduce load on your Matomo server. Your agent can be programmed to make this choice based on the context.

Q: Does this Matomo Alternative MCP Server work with WordPress sites in LangChain?

It does. The getwpprocessedreport tool is specifically designed to pull analytics data through the WordPress REST API, which is useful if your Matomo instance is integrated that way.

Get your LangChain agent tracking site analytics. Build chains that report on user behavior and campaign performance automatically.

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Connect Matomo Alternative MCP to LangChain

Create your Vinkius account to connect Matomo Alternative to LangChain 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 LangChain

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Chain Tracking and Reporting

Your agent can now track user activity with precision. Use `track_action` to fire off a single conversion event the moment it happens, or queue up interactions and send them all at once with `track_bulk` to reduce network chatter. This isn't just fire-and-forget; it's the first link in your chain. After tracking, your agent can immediately confirm the results. The next step in the chain could be a call to `get_visits_summary` to check if the new visit or action count is reflected. This creates a closed loop where your agent acts, then verifies, all in one sequence.

Generate Reports On-the-Fly

Pull detailed analytics right into your agent's context. A call to `get_processed_report` gives your agent the raw numbers—visits, bounce rates, conversion details—for a specific period. It can parse this data to decide what to do next, like flagging a drop in traffic. Your agent can also create visuals. Use `get_image_graph` to generate a PNG of a traffic trend graph. That binary data can be saved to a file, passed to another tool, or embedded in a report, turning abstract numbers into something a human can actually see.

Adaptive Analytics with this MCP Server

Your agent doesn't need to have every report hard-coded. Start a chain with `get_report_metadata` and your agent gets a full list of all available reporting functions directly from your Matomo instance. It's a dynamic way for your agent to discover its own capabilities. This lets you build agents that adapt. If a new custom report is added to Matomo, the agent sees it on the next run and can use it without you changing any code. It makes your analytics chains more resilient and less brittle. This MCP server handles the connection.

Setup guide

Set up Matomo Alternative MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Matomo Alternative tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "matomo-alternative-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Matomo Alternative transactions"
    })
    print(result["messages"][-1].content)

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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 Matomo. 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 Matomo Alternative MCP in LangChain

Install the adapter with `pip install langchain-mcp-adapters`. Then, instantiate `MultiServerMCPClient` with your Vinkius endpoint URL, call `.get_tools()`, and pass the resulting list to your agent factory.

Yes. A common chain is to call `get_visits_summary`, format the numbers into a string, and then pass that string to an email or Slack tool. The agent orchestrates the whole sequence.

Use `track_action` for critical, real-time events like a purchase. Use `track_bulk` for less critical actions or high-volume logging to reduce load on your Matomo server. Your agent can be programmed to make this choice based on the context.

It does. The `get_wp_processed_report` tool is specifically designed to pull analytics data through the WordPress REST API, which is useful if your Matomo instance is integrated that way.

Vinkius runs this server in an ephemeral sandbox for each request. The server doesn't store your `page view` or `ecommerce action` data; it just proxies the request to your own Matomo instance using the token you provide.

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