How to Use the Descope (Auth Platform) MCP in LangChain
LangChain agents run multi-step authentication and tenant onboarding pipelines using Descope (Auth Platform) tools.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Descope (Auth Platform) MCP to LangChain
Create your Vinkius account to connect Descope (Auth Platform) 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.
Chain Descope (Auth Platform) signups with LangChain
LangChain agents use `auth_otp_signup_email` to kick off email-based registrations directly inside your active run. The tool handles sending the code, and your agent waits for the response to trigger the verification step. Once verified via `auth_otp_verify_email`, the chain feeds the output into `mgmt_create_user` to establish the profile. You watch the entire transition inside LangSmith to verify execution order.
Provision tenants inside LangChain reasoning loops
Your LangChain agent evaluates incoming organization requests and runs `mgmt_create_tenant` to spin up isolated spaces. This MCP Server lets the agent determine the tenant structure dynamically before assigning security parameters. The pipeline continues as the agent calls `mgmt_create_role` and `mgmt_create_permission` to lock down the tenant. Every action gets traced in LangSmith so you can audit permissions.
Run passwordless flows in LangChain ReAct loops
Handling complex sign-ins is straightforward when your LangChain agent executes `auth_enchantedlink_signup` to initiate a secure login. The agent pauses, polls the session using `auth_enchantedlink_poll`, and processes the result. If the poll succeeds, the agent triggers `auth_enchantedlink_verify` to validate the user. This multi-server MCP setup keeps your auth logic inside a single conversational run.
Set up Descope (Auth Platform) 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 Descope (Auth Platform) 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({
"descope-auth-platform-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 Descope (Auth Platform) 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 Descope. 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 Descope (Auth Platform) MCP in LangChain
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