How to Use the Metabase (Business Intelligence & Analytics) MCP in CrewAI

Q: How does a CrewAI team search through Metabase (Business Intelligence & Analytics) content?

The search agent uses searchcontent to crawl your BI entities. It returns a list of matching reports to the crew for further investigation.

Q: How do I expose Metabase (Business Intelligence & Analytics) tools to a specific agent?

You use the toolfilter parameter in your crew setup. This allows you to restrict which agents have access to specific BI operations.

Deploy a specialized CrewAI team to monitor and analyze your Metabase (Business Intelligence & Analytics) reports.

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Connect Metabase (Business Intelligence & Analytics) MCP to CrewAI

Create your Vinkius account to connect Metabase (Business Intelligence & 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 Metabase (Business Intelligence & Analytics) with CrewAI

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Perplexity

Autonomous BI monitoring

Assign a dedicated monitor agent to keep an eye on your dashboard health. By using `list_dashboards`, the agent tracks the current inventory of reports and flags any missing or broken links. It ensures your BI environment stays clean. When a new dashboard is created, the agent logs it into your shared memory for the rest of the crew.

Multi-agent data research

Let one agent search while another analyzes. Your research agent uses `search_content` to find relevant reports, then passes the card details to an analyst agent for interpretation. This divides the labor of complex data tasks. You get faster answers because your crew works in parallel to resolve data requests.

Visual question retrieval

Your agents interact with the visual logic of your BI platform using `get_card`. They extract the raw queries and parameters needed to understand where your numbers originate. This builds deep transparency into your reporting. The agents verify the logic behind every chart before presenting it to you.

Setup guide

Set up Metabase (Business Intelligence & 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 Metabase (Business Intelligence & Analytics) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Metabase (Business Intelligence & 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="Metabase (Business Intelligence & Analytics) Analyst",
        goal="Access and analyze Metabase (Business Intelligence & Analytics) data via MCP.",
        backstory="Expert analyst with direct Metabase (Business Intelligence & Analytics) access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Metabase (Business Intelligence & 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 Metabase. 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 Metabase (Business Intelligence & Analytics) MCP in CrewAI

The search agent uses `search_content` to crawl your BI entities. It returns a list of matching reports to the crew for further investigation.

No, the MCP server is read-only. Your agents are strictly limited to listing and retrieving data, keeping your BI configurations safe from accidental changes.

You use the tool_filter parameter in your crew setup. This allows you to restrict which agents have access to specific BI operations.

Yes, the MCP server handles multiple simultaneous calls. Your crew agents can fetch different dashboards or cards at the same time without locking.

The server authenticates each request via your endpoint token. Your BI data is never stored on the server, ensuring direct communication between your crew and the platform.

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