How to Use the Mode (Collaborative Data Platform) MCP in CrewAI

Q: How do I search reports in Mode (Collaborative Data Platform) with CrewAI?

You add searchreports to your agent tools. The crew then performs keyword searches to find the right reports for their assigned task.

Q: Does CrewAI support Mode (Collaborative Data Platform) member lists?

It does. By using listmembers, your crew can identify stakeholders for any given report or project space.

Q: Can CrewAI use Mode (Collaborative Data Platform) to organize spaces?

You use listspaces to help the crew understand the current setup. They can then categorize reports based on the space information they receive.

Deploy a specialized crew to manage your Mode (Collaborative Data Platform) workspace with CrewAI.

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Connect Mode (Collaborative Data Platform) MCP to CrewAI

Create your Vinkius account to connect Mode (Collaborative Data Platform) 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 (Collaborative Data Platform) with CrewAI

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Role-based workspace monitoring with CrewAI

Assign an agent to audit your environment using `list_reports` and `list_spaces`. One agent tracks report usage while another handles the organization. This teamwork removes the burden from your human analysts. The crew coordinates to ensure the workspace remains organized and functional.

Autonomous data source validation for CrewAI

Let your researchers call `list_data_sources` to verify warehouse connectivity before starting an analysis. If a source is disconnected, the agent reports it to the moderator. This prevents failed query attempts. The agents verify the environment before they act, keeping the workflow moving.

Deep analytical exploration for CrewAI

Use `get_report` to pull specific parameters for your analytical agents. They analyze the metadata to understand the report's purpose and logic. This gives your crew the context needed to make informed decisions. They work with the same data your analysts see every day.

Setup guide

Set up Mode (Collaborative Data Platform) 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 (Collaborative Data Platform) tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Mode (Collaborative Data Platform) 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. 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 (Collaborative Data Platform) MCP in CrewAI

You add `search_reports` to your agent tools. The crew then performs keyword searches to find the right reports for their assigned task.

It does. By using `list_members`, your crew can identify stakeholders for any given report or project space.

You use `list_spaces` to help the crew understand the current setup. They can then categorize reports based on the space information they receive.

The server uses a single endpoint token for all communication. This keeps your credentials out of the agent's memory and ensures a secure handshake.

The server only exposes non-sensitive metadata about your reports and spaces. It acts as a controlled gateway, ensuring your core business data is never exposed.

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