How to Use the Umami Cloud MCP in LangChain

Q: Does Umami Cloud support complex data structures with LangChain?

Yes. The websites tool returns structured data covering multiple dimensions—like browser, OS, and specific URLs—which your agent can parse and act upon immediately.

Build multi-step analytics chains with LangChain, using Umami Cloud MCP Server output.

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Connect Umami Cloud MCP to LangChain

Create your Vinkius account to connect Umami Cloud 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 Umami Cloud with LangChain

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Track active user count via `users`

The `users` tool gives you the current number of active website users. Your agent calls this function and immediately gets a clean integer value, which it can then use in subsequent steps. This output allows your chain to make decisions based on real-time traffic volume—for instance, deciding whether to call another API endpoint only if user count exceeds 100.

Analyze site metrics using `websites`

Need details about specific website visitors? The `websites` tool collects deep metrics like URLs, operating systems, and browsers. Your agent executes this call to get structured data arrays. This lets you build complex pipelines that segment users—for example, grouping all visits from Safari using an iOS device type.

Combine analytics in one chain

You can combine both metrics tools into a single reasoning pipeline. First, the agent calls `users` to check overall volume. If that number is high, it then calls `websites` to drill down and find specific browser types. The result is a multi-step process where the output of one tool call dictates the parameters for the next, giving you deep context on traffic spikes.

Setup guide

Set up Umami Cloud 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 Umami Cloud 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({
    "umami-cloud-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 Umami Cloud transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Umami Cloud MCP in LangChain

Umami Cloud provides tools that act as endpoints in your chain. Your agent calls `users` or `websites`, and the resulting data is passed directly to the next step, just like any other output.

Yeah, absolutely. Since your agent controls the flow, you can build decision points: only proceed with a database write if the `users` tool reports activity above a certain threshold.

The server provides two main tools. You get an active user count via `users`, and detailed visitor metrics, including device type, OS, and URL path, using the `websites` tool.

Yes. The `websites` tool returns structured data covering multiple dimensions—like browser, OS, and specific URLs—which your agent can parse and act upon immediately.

It touches web traffic metrics. Specifically, it provides counts for active users and detailed records of visitor attributes like browsers, operating systems, and visited URLs.

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