How to Use the Middesk MCP in LangChain

Chain Middesk verification steps directly in LangChain agents to automate your entire KYB pipeline without manual interference.

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Connect Middesk MCP to LangChain

Create your Vinkius account to connect Middesk 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 Middesk with LangChain

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Automate business identity checks

Start your pipeline with `autocomplete_identity` to pull legal names and registration details directly into your agent's state. This removes the need for manual data entry and keeps your chain moving forward. Once the agent identifies the entity, `create_business` initializes the record. Your agent handles the heavy lifting while you define the logic for how each piece of data flows through the chain.

Verify tax and legal status

Chain `get_tax_registration` after the initial lookup to confirm a business is in good standing. LangChain processes the output immediately to decide if the next step is approval or further investigation. If the agent needs more evidence, it triggers `list_documents` automatically. You get full observability in LangSmith, so you see exactly why a business was flagged or cleared.

Prefill data for speed

Use `prefill_business` to minimize user input errors during onboarding. By feeding website metadata directly into the tool, your agent generates accurate records in milliseconds. This creates a tighter loop between your frontend and the verification backend. Your LangChain agents now make decisions based on live, verified state registry data.

Setup guide

Set up Middesk 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 Middesk 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({
    "middesk-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 Middesk transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Middesk. 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 Middesk MCP in LangChain

Install the required adapters and initialize the client using the server URL. You then pass the tool list directly into your agent constructor to enable full access to the Middesk MCP Server.

Yes, you can build multi-step chains where the agent chooses the next tool based on prior results. This allows for conditional logic based on tax registrations or document availability.

Vinkius manages the connection via a secure endpoint token. Your agent only interacts with the data you explicitly permit through the tool definitions.

It does. You can use the client session feature to maintain context across multiple agent turns if your workflow requires persistent data tracking.

The server retrieves documents through specific tool calls that only the agent can execute. Data remains isolated within the Vinkius sandbox environment during the entire verification process.

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