How to Use the eSignly Electronic Signature MCP in LangChain
Build smart document pipelines in LangChain by connecting eSignly signature tracking and audit tools directly to your ReAct agents.
Works with every AI agent you already use
…and any MCP-compatible client
Connect eSignly Electronic Signature MCP to LangChain
Create your Vinkius account to connect eSignly Electronic Signature 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.
LangChain MCP Server Integration
The eSignly MCP Server feeds live document states straight into your ReAct agents. You call `list_esign_documents` to grab active contracts, then chain the output into `get_document_detailed_data` to inspect specific settings. LangChain handles the reasoning. Your agent reads the status, decides if it needs more context, and executes the next tool call automatically. You track every step, latency, and token cost through LangSmith.
Automated Audit Trail Chains
Compliance checks require specific data points to prove non-repudiation. Your pipeline triggers `list_document_audit_trail` to pull the exact timeline of a contract directly from the API. If a signature looks suspicious, the agent chains that data into `list_document_signers`. It cross-references the current signing status against the audit log, giving your team a definitive answer on who touched the file and when.
Template and Volume Tracking
Managing hundreds of standard contracts requires visibility across your entire account. You use `list_esign_templates` to pull available forms and `quick_signing_volume_audit` to check daily activity. LangChain agents take these metrics and format them into daily reports. You get a clear picture of your signing volume without manually logging into the dashboard.
Set up eSignly Electronic Signature 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 eSignly Electronic Signature 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({
"esignly-electronic-signature-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 eSignly Electronic Signature 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 eSignly Electronic Signature. 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 eSignly Electronic Signature MCP in LangChain
Use it with your favorite AI tools
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