How to Use the Clustdoc MCP in LangChain

Q: How do I list Clustdoc dossiers using LangChain?

Use the listclientdossiers tool within your agent definition. It returns the current state of your applications directly into your execution chain.

Q: Can LangChain automate Clustdoc invitation emails?

Yes, you can configure your agent to call sendonboardinginvitation automatically. It relies on the dossier ID to trigger the correct email to your client.

Build multi-step onboarding chains in LangChain by linking Clustdoc tools directly into your reasoning pipelines.

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Connect Clustdoc MCP to LangChain

Create your Vinkius account to connect Clustdoc to LangChain 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 LangChain

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Chain Clustdoc tools for automated onboarding flows

Connect your agents to your client data by piping outputs from `list_client_dossiers` directly into follow-up tasks. You define the logic that triggers the next step without manual intervention. Your agent inspects the progress of any application and decides when to fire `send_onboarding_invitation` based on real-time status. This keeps your pipeline moving while maintaining full observability via LangSmith.

Deploy Clustdoc MCP Server within your graph

Integration is straightforward using the standard adapters. You fetch tools through the client and inject them into your agent's execution loop. The system handles the heavy lifting, allowing you to focus on the reasoning logic. You build complex agents that verify status through `get_application_status_details` and adjust workflow configurations on the fly.

Manage onboarding templates programmatically

Access your entire library of workflows by calling `list_onboarding_templates` inside your chain. You get immediate visibility into available structures for new client setups. Once a template is selected, your agent triggers `launch_new_onboarding` to start the process. Everything stays in your controlled execution environment, ensuring your agents track exactly what happens during the lifecycle.

Setup guide

Set up Clustdoc MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Clustdoc tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "clustdoc-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Clustdoc transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Clustdoc MCP in LangChain

Use the `list_client_dossiers` tool within your agent definition. It returns the current state of your applications directly into your execution chain.

Yes, you can configure your agent to call `send_onboarding_invitation` automatically. It relies on the dossier ID to trigger the correct email to your client.

Your Clustdoc data stays protected behind standard API authentication. The MCP Server only touches personal identifying information like dossier IDs and client email addresses during authorized tool execution.

It does if you use the client session feature. This maintains state across your LangChain steps, which is helpful for long-running onboarding processes.

Since you are using LangSmith, every tool call shows up in your traces. You see the exact inputs and outputs for every Clustdoc function you run.

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