How to Use the Vanta MCP in LangChain
Run complex Vanta workflows and decision chains using LangChain.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Vanta MCP to LangChain
Create your Vinkius account to connect Vanta 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.
Audit Readiness Check
You can build a full compliance workflow. First, run `vanta_compliance_status` to check the overall posture across SOC 2, HIPAA, and GDPR. If you see critical alerts, your agent then calls `vanta_list_tests` to pinpoint which specific controls are failing, guiding you directly to the problem area.
Endpoint Compliance Audit
Start by calling `vanta_list_computers` to get an inventory of every monitored device. The output reveals OS versions and whether disk encryption is enabled. From there, you can use `vanta_list_people` to cross-reference who owns those devices and if their security training is overdue. This gives a complete view of endpoint risk.
Risk Identification Pipeline
Need to report on high-risk areas? First, run `vanta_list_risks` to pull the entire risk register. The resulting data, including impact scores and owners, can then be fed into an agent that checks for mitigating controls using `vanta_list_policies`. This helps you prioritize remediation.
Set up Vanta 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 Vanta 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({
"vanta-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 Vanta 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 Vanta. 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 Vanta MCP in LangChain
Use it with your favorite AI tools
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Start using the Vanta MCP today
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