How to Use the Ugosign MCP in LangChain
Build multi-step automation chains for LangChain.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Ugosign MCP to LangChain
Create your Vinkius account to connect Ugosign 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.
Automate Signature Workflows
Start by calling `list_documents` to gather a list of files. Then, pass the necessary details into `create_signature_request`. This lets your agent chain together data retrieval and action execution in one go. Your multi-step reasoning pipeline determines when these calls run. The output from listing documents automatically informs the input for creating the signature request.
Verify Document Statuses
Need to check if a document is ready or where it stands? Use `get_document` to pull full file details, then follow up with `get_signature_request`. This allows your agent to confirm both the asset and its current lifecycle stage. Observing these steps helps you build complex chains. Your agent can decide: 'If document status is X, then call `get_signature_request`.' It's all about flow control.
Build Contextual Requests
You can pull necessary context before signing. First, use `get_organization` to get the proper company details. Next, pass this verified data into a new signature workflow using `create_signature_request`. This ensures the request has all required party information. This pattern lets your agent act like an expert user. It doesn't just call tools; it gathers prerequisites first.
Set up Ugosign MCP in LangChain
Prerequisites
- Python 3.10+ installed
-
langchain-mcp-adapters+langgraphpackages - 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 LangChainBaseToolobjects. - 2
Connect via HTTP transport
Use
MultiServerMCPClientwith"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 Ugosign tool calls through the MCP protocol. - 4
Run with any LLM
Swap
ChatOpenAIforChatAnthropic,ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.
from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI
async with MultiServerMCPClient({
"ugosign-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 Ugosign transactions"
})
print(result["messages"][-1].content) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Ugosign. 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.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about Ugosign MCP in LangChain
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