How to Use the Umami (Privacy Analytics) MCP in CrewAI

Q: How do I ensure Umami (Privacy Analytics) is ready for complex tasks with CrewAI?

Before running a full workflow, you should always use the verifytoken tool. This confirms that all necessary credentials are available to your autonomous agents.

Q: Can Umami (Privacy Analytics) report on website metrics when used with CrewAI?

The server provides multiple metric functions, like getwebsitemetrics and getwebsitestats. Your crew can call these to gather data for the final comprehensive analysis.

Run autonomous, role-based analytics operations with CrewAI and Umami (Privacy Analytics).

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Connect Umami (Privacy Analytics) MCP to CrewAI

Create your Vinkius account to connect Umami (Privacy Analytics) to CrewAI 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 (Privacy Analytics) with CrewAI

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Perplexity

Automated Analytics Research

Assign a 'Researcher' agent to gather data by calling `get_website_event_data`. This specialized role collects event names and counts, building the foundational knowledge for the team. A second 'Analyst' agent can then take this raw output and generate actionable insights using tools like `create_funnel_report`.

Multi-Step Website Management

Build a full operational cycle. A 'Manager' agent can first check site status with `get_website_active`, then decide if the data needs cleaning by calling `reset_website`. After cleanup, another agent can restore tracking capability by using `create_link` or `create_pixel`.

Autonomous Reporting Pipelines

Let your crew run complex reporting tasks. One agent gathers site metrics via `get_website_metrics_expanded`, while a moderator agent compiles it all into a final deliverable using `list_reports`. The system can also monitor user activity by calling `get_website_sessions_stats`, providing the necessary context for the report.

Setup guide

Set up Umami (Privacy Analytics) MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Umami (Privacy Analytics) tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Umami (Privacy Analytics) Analyst",
    goal="Access and analyze Umami (Privacy Analytics) data via MCP.",
    backstory="Expert analyst with direct Umami (Privacy Analytics) access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Umami (Privacy Analytics) transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Umami (Privacy Analytics) Analyst",
        goal="Access and analyze Umami (Privacy Analytics) data via MCP.",
        backstory="Expert analyst with direct Umami (Privacy Analytics) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Umami (Privacy Analytics) transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Umami. 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 Umami (Privacy Analytics) MCP in CrewAI

The MCP Server provides specific tools that agents can execute in sequence. This allows a dedicated agent to watch sessions via `get_session_activity` and take recorded action.

Yes, you can assign roles for moderation over users. Tools like `list_users` and `admin_list_users` give your crew the necessary overview to manage access.

The server handles event data, session details, and user identifiers. The `get_user` tool retrieves specific account information which your crew can analyze.

Before running a full workflow, you should always use the `verify_token` tool. This confirms that all necessary credentials are available to your autonomous agents.

The server provides multiple metric functions, like `get_website_metrics` and `get_website_stats`. Your crew can call these to gather data for the final comprehensive analysis.

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