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

Q: How do my AutoGen agents collaborate using Metabase (Business Intelligence & Analytics) tools?

One agent uses listdashboards to find outdated reports, while a second agent calls getdashboard to analyze the layout. They discuss the findings in a group chat to decide if a dashboard needs cleanup.

Q: Can AutoGen agents find duplicate charts in Metabase (Business Intelligence & Analytics)?

Yes, your agents use listcards to fetch the full list of visual questions, then write a comparison script. They use getcard to compare the underlying SQL queries and flag identical logic.

Q: How do I register these Metabase (Business Intelligence & Analytics) tools with an AutoGen agent?

You use mcpservertools with your Vinkius HTTP URL to fetch the tool definitions. Then, you pass this list directly to your AssistantAgent constructor during initialization.

Q: Does this integration support the AutoGen multi-agent conversation pattern?

Yes, any agent in your group chat can call tools like listcollections or searchcontent when it needs data. The tool execution results are shared back into the conversation for other agents to analyze.

Let your AutoGen agents debate metric definitions and verify dashboard layouts using this Metabase MCP Server.

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Connect Metabase (Business Intelligence & Analytics) MCP to AutoGen

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

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Resolve Metric Discrepancies via AutoGen Agent Debates

The `get_card` tool pulls the exact SQL query and mapping logic behind a specific visual question for your agents to analyze. An analyst agent and a data engineer agent can then debate whether the query matches your business definitions — and this matters — because metric drift ruins board meetings. They use `list_databases` to check if the card points to the correct production database. This multi-agent verification ensures that your team only relies on validated, accurate metrics.

Automate Dashboard Auditing with AutoGen MCP Server Teams

The `list_dashboards` tool fetches your entire dashboard inventory so your AutoGen agents can audit them. One agent lists the boards, while another checks for outdated layouts. The auditor agent calls `get_dashboard` to inspect the layout matrices of suspicious boards. This lets your agent team flag messy, overlapping, or broken dashboards without human oversight.

Coordinate Global Content Searches Across Departments

The `search_content` tool allows your AutoGen coordinator agent to run broad searches across all your folders and cards. The coordinator then passes relevant matches to specialized sub-agents. These sub-agents use `list_collections` to verify that the discovered reports are sitting in the correct department folders. It automates the cleanup of messy, sprawling BI workspaces.

Setup guide

Set up Metabase (Business Intelligence & Analytics) MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Metabase (Business Intelligence & Analytics) tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Metabase (Business Intelligence & Analytics)_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Metabase (Business Intelligence & Analytics) data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Metabase (Business Intelligence & Analytics)_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Metabase (Business Intelligence & Analytics) data")
    print(result.messages[-1].content)

Get your connection token →

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Common questions about Metabase (Business Intelligence & Analytics) MCP in AutoGen

One agent uses `list_dashboards` to find outdated reports, while a second agent calls `get_dashboard` to analyze the layout. They discuss the findings in a group chat to decide if a dashboard needs cleanup.

Yes, your agents use `list_cards` to fetch the full list of visual questions, then write a comparison script. They use `get_card` to compare the underlying SQL queries and flag identical logic.

You use `mcp_server_tools` with your Vinkius HTTP URL to fetch the tool definitions. Then, you pass this list directly to your `AssistantAgent` constructor during initialization.

Yes, any agent in your group chat can call tools like `list_collections` or `search_content` when it needs data. The tool execution results are shared back into the conversation for other agents to analyze.

This MCP integration only accesses dashboard layouts, collection folder names, and card SQL configurations. All communication goes through a zero-trust sandbox, preventing unauthorized access to your source databases.

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