How to Use the Clustdoc MCP in CrewAI

Q: Can multiple CrewAI agents collaborate on a single Clustdoc dossier?

Yes. Your intake agent can find a dossier using listclientdossiers, and your manager agent can assign a team member using listclustdocteams.

Q: How do I restrict which Clustdoc tools a CrewAI agent can use?

Use the MCPServerHTTP class from the MCP package with a toolfilter. This prevents your communication agent from launching new onboardings while allowing it to send invites.

Q: Can my crew read my Clustdoc team profiles?

Yes. The getmyclustdocprofile tool lets your agent verify account details to ensure all actions are logged under the correct user.

Deploy a team of specialized CrewAI agents to manage your Clustdoc dossiers and send onboarding invites automatically.

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Create your Vinkius account to connect Clustdoc 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 Clustdoc with CrewAI

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Role-based dossier coordination with CrewAI

The `list_client_dossiers` tool gives your intake agent a clear view of incoming applications. This agent identifies which dossiers need attention and passes them to the follow-up agent. To find missing files, the follow-up agent calls `get_application_status_details`. By splitting the work, your crew processes files faster than a single agent could.

Automated onboarding dispatch

Spinning up new customer portals is handled by the `launch_new_onboarding` tool. Your setup agent coordinates with your CRM agent to fetch client details first. Once the portal is ready, the communications agent invokes `send_onboarding_invitation` to email the client. The agent then logs the timestamp in your shared crew memory.

Workflow analysis via this MCP Server

Inspecting your current onboarding structures is easy with the `list_onboarding_templates` tool. Your analyst agent determines which template fits the client's industry via this MCP Server. It then uses `get_workflow_configuration` to extract the required document list. This allows the crew to prepare the client for what they need to upload.

Setup guide

Set up Clustdoc 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 Clustdoc tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Clustdoc transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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="Clustdoc Analyst",
        goal="Access and analyze Clustdoc data via MCP.",
        backstory="Expert analyst with direct Clustdoc access.",
        tools=mcp_tools,
    )

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

Pass your Vinkius URL into the agent's MCP configuration. This exposes tools like `list_client_dossiers` directly to that specific agent's toolbox.

Yes. Your intake agent can find a dossier using `list_client_dossiers`, and your manager agent can assign a team member using `list_clustdoc_teams`.

Use the `MCPServerHTTP` class from the MCP package with a `tool_filter`. This prevents your communication agent from launching new onboardings while allowing it to send invites.

Yes. The `get_my_clustdoc_profile` tool lets your agent verify account details to ensure all actions are logged under the correct user.

Your local python crew processes the dossier status and client details in memory. Vinkius handles the MCP Server transport securely, never storing your client's personal identification documents.

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