How to Use the Digify MCP in LangChain

Q: Can I use Digify with LangChain agents to auto-provision data rooms?

Yes. You use createdataroom inside your agent's tools definition, allowing the model to spin up secure environments when client onboarding triggers.

Q: Can I trace Digify tool calls in LangChain runs with LangSmith?

Yes, every execution of tools like listactivities or getfile shows up in your LangSmith dashboard. You get full visibility into latency, payload sizes, and raw JSON outputs.

Q: How do I pass multiple MCP server tools to my LangChain client?

You initialize the MultiServerMCPClient with the Digify endpoint alongside other servers. The client aggregates all tools, giving your agent a unified toolkit.

Track every document view and secure files directly inside your LangChain agent workflows with this MCP Server.

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Connect Digify MCP to LangChain

Create your Vinkius account to connect Digify 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 Digify with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Automate secure file sharing in LangChain chains

Your agent calls `protect_file` to lock down PDFs before passing them to external vendors. It instantly applies dynamic watermarks and sets up access rules based on current run variables. You feed this output directly into the next chain step. No manual steps or context switching needed to keep your IP safe.

Build autonomous deal rooms with LangChain

The `create_dataroom` and `invite_guest` tools let your LangChain agents build isolated document vaults on the fly. When a new lead signs a preliminary agreement, the agent provisions the room and emails the access link. LangSmith monitors the whole sequence. You see exactly when the agent created the room and which guest got invited without guessing.

Real-time activity audits inside your MCP Server

Run `list_activities` and `get_dataroom_stats` to track who opened what and how long they stayed. Your agent parses this telemetry to score lead interest or flag security anomalies. This converts raw telemetry into structured steps. If a guest downloads a file, the chain triggers an alert or updates your database instantly.

Setup guide

Set up Digify 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 Digify 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({
    "digify-alternative-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 Digify 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 Digify. 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 Digify MCP in LangChain

Yes. You use `create_dataroom` inside your agent's tools definition, allowing the model to spin up secure environments when client onboarding triggers.

The MCP adapter catches API exceptions and returns them as text to the LLM. Your agent then decides whether to retry or alert an administrator.

Yes, every execution of tools like `list_activities` or `get_file` shows up in your LangSmith dashboard. You get full visibility into latency, payload sizes, and raw JSON outputs.

You initialize the `MultiServerMCPClient` with the Digify endpoint alongside other servers. The client aggregates all tools, giving your agent a unified toolkit.

Your actual documents never pass through Vinkius or the LLM context unless you explicitly fetch them. The server only handles metadata like file IDs and access permissions, keeping your intellectual property isolated in your Digify account.

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