How to Use the Clustdoc MCP in CrewAI

Deploy a specialized agent crew to manage your Clustdoc intake with CrewAI.

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Connect Clustdoc MCP to CrewAI

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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Run Clustdoc operations with CrewAI

Assign a dedicated agent to run `list_applications` and categorize submissions. The agent identifies which clients need follow-ups while you focus on high-level tasks. Your crew shares memory of the intake state, allowing them to collaborate. One agent identifies a missing file, and the next sends the notification.

Scale Clustdoc intake using CrewAI

Use `create_application` to bulk-generate onboarding requests for new batches of clients. Your agents can handle hundreds of requests without getting tired or missing a step. This MCP Server provides the tools to push data directly into your intake flow. Your agents operate autonomously, following your defined sequence of operations.

Audit Clustdoc teams via CrewAI

Use `list_team_members` to verify who is currently overseeing your active onboarding projects. The agent can report back on resource allocation issues. If the workload is uneven, the agent can flag this for human review. It maintains a clear view of your internal operations by querying the server periodically.

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)

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="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

Yes, you assign the tools to specific agents. One agent can monitor the workflow while another takes action on the applications.

Pass the server URL to your agent definition. The framework handles the connection so your agents can invoke the tools during their tasks.

It does. You can set a manager agent to oversee the intake process and delegate specific tasks to agents equipped with these tools.

You can limit which agents have access to which tools. This prevents junior agents from creating applications while allowing them to read existing data.

Your document intake records are encrypted in transit. The server runs in a zero-trust environment where only your authenticated agents can interact with the data.

Use it with your favorite AI tools

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