How to Use the Zoho WorkDrive MCP in CrewAI

Q: How can I audit Zoho WorkDrive permissions using CrewAI?

You assign one agent the task of calling listfilepermissions on a target folder. The specialized agent then analyzes that list, flagging any accounts that shouldn't have access.

Q: What if I need to check file details in Zoho WorkDrive with CrewAI?

Use one agent solely for reading metadata. It calls getfilemetadata, ensuring the data is consistently gathered before passing it off to another agent for analysis.

Automate deep file audits using specialized agents with CrewAI.

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Connect Zoho WorkDrive MCP to CrewAI

Create your Vinkius account to connect Zoho WorkDrive 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 Zoho WorkDrive with CrewAI

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Multi-Agent Zoho WorkDrive Audits with crewai

Don't run one agent; use a team. Assign Agent A to list all teams (`list_teams`), and assign Agent B to take that output and check the folder structure for each using `list_team_folders`. Agent C then acts as the final reporting layer, compiling the findings into a single report without human intervention.

Advanced file monitoring with MCP Server and crewai

Need to know what's happening? Set up a monitor agent. It can run `list_files` across multiple target folders, then pass that list to an analysis agent which checks the metadata (`get_file_metadata`) for compliance issues. This role-based specialization makes complex investigations manageable.

Automating content lifecycle using Zoho WorkDrive with crewai

The process is sequential: Agent A lists current files, Agent B reviews the permissions (`list_file_permissions`) and identifies outdated access rights. Finally, a moderator agent uses `delete_file` to safely remove unnecessary assets. It's full automation for asset cleanup.

Setup guide

Set up Zoho WorkDrive 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 Zoho WorkDrive tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

    task = Task(
        description="List recent Zoho WorkDrive 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 Zoho WorkDrive. 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 Zoho WorkDrive MCP in CrewAI

You assign one agent the task of calling `list_file_permissions` on a target folder. The specialized agent then analyzes that list, flagging any accounts that shouldn't have access.

Yes. You can set up agents to collaboratively manage content—one listing files and another renaming them using `rename_file` based on a naming convention you provide.

Absolutely. By chaining tools, you can build an audit that first uses `list_teams`, then iterates through the folders using `list_team_folders` and checks permissions at each step.

Use one agent solely for reading metadata. It calls `get_file_metadata`, ensuring the data is consistently gathered before passing it off to another agent for analysis.

This server touches file structure and access control lists (ACLs). It manages information about files, folders, team workspaces, and which users have rights within Zoho WorkDrive.

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