How to Use the Mode Analytics MCP in CrewAI

Q: How do CrewAI agents collaborate on Mode Analytics reports?

One agent can find reports using listmodereports, while another triggers them via runmodereport. They share context and memory to execute complex data workflows.

Q: Can I limit which Mode Analytics tools a CrewAI agent can access via this MCP Server?

Yes. You can use the toolfilter option in CrewAI's MCPServerHTTP to expose only specific tools, like listmodereports, while hiding execution tools.

Deploy a crew of specialized CrewAI agents to audit, monitor, and run your Mode Analytics reports completely autonomously.

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Connect Mode Analytics MCP to CrewAI

Create your Vinkius account to connect Mode 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 Mode Analytics with CrewAI

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Coordinate multi-agent reporting teams

CrewAI lets you split complex data tasks among highly specialized agents. This MCP connection lets one agent act as a workspace auditor, listing all active spaces with `list_mode_spaces` and reports with `list_mode_reports`. A second analyst agent can then inspect report definitions using `get_mode_report` to identify which datasets need updates. This division of labor prevents single-agent bottlenecks. Your agents collaborate in real-time, sharing memory to ensure no report is overlooked or run unnecessarily.

Run and audit reports via this CrewAI MCP Server

Automate your daily reporting cycles with zero human intervention. A coordinator agent triggers report runs using `run_mode_report`, while a monitoring agent tracks the run status via `get_mode_report_run`. If a run fails, the monitoring agent can inspect the underlying SQL using `list_mode_queries` to diagnose the issue. This creates a self-healing pipeline that keeps your business intelligence tools up to date.

Audit workspace access and query schemas

Keep your data warehouse secure and organized. Your crew can use `list_mode_members` to audit access across your analytics workspace. Meanwhile, another agent can pull calculated field definitions using `list_mode_definitions`. This ensures your team uses consistent business logic across all dashboards.

Setup guide

Set up Mode 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 Mode Analytics tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Mode 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 Mode Analytics. 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 Mode Analytics MCP in CrewAI

One agent can find reports using `list_mode_reports`, while another triggers them via `run_mode_report`. They share context and memory to execute complex data workflows.

Yes. You can use the `tool_filter` option in CrewAI's `MCPServerHTTP` to expose only specific tools, like `list_mode_reports`, while hiding execution tools.

Agents run asynchronously. An agent will trigger a run with `run_mode_report` and poll `get_mode_report_run` in the background, allowing other crew members to continue their tasks.

This integration supports stdio, SSE, and Streamable HTTP transports. You can pass the connection URL directly into your agent's `mcps` configuration list.

All data transmission is encrypted in transit. The server runs in a zero-trust, ephemeral V8 isolate sandbox, meaning your SQL queries and member lists are never cached or stored.

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