4,000+ servers built on vurb.ts
Vinkius

SuperTokens MCP Server for LangChainGive LangChain instant access to 18 tools to Assign Role To User, Bulk Import Users, Create Or Update Role, and more

MCP Inspector GDPR Free for Subscribers

LangChain is the leading Python framework for composable LLM applications. Connect SuperTokens through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Ask AI about this MCP Server for LangChain

The SuperTokens MCP Server for LangChain is a standout in the Developer Tools category — giving your AI agent 18 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

ClaudeClaude
ChatGPTChatGPT
CursorCursor
GeminiGemini
WindsurfWindsurf
VS CodeVS Code
JetBrainsJetBrains
VercelVercel
+ other MCP clients
python
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "supertokens": {
            "transport": "streamable_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,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using SuperTokens, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
SuperTokens
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About SuperTokens MCP Server

Connect your SuperTokens Core instance to any AI agent to manage user lifecycles, session security, and Role-Based Access Control (RBAC) through natural language.

LangChain's ecosystem of 500+ components combines seamlessly with SuperTokens through native MCP adapters. Connect 18 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

  • User Management — Sign up new users, sign in existing ones, and retrieve detailed user profiles or link multiple accounts together.
  • Session Control — Create, refresh, and revoke sessions (JWT or database-backed) to maintain tight security over user access.
  • RBAC & Permissions — Create roles, define permissions, and assign them to users to manage authorization levels dynamically.
  • User Metadata — Store and update custom JSON metadata for users to track preferences or application-specific data.
  • Account Linking — Seamlessly link or unlink different recipe user IDs to a primary user identity.

The SuperTokens MCP Server exposes 18 tools through the Vinkius. Connect it to LangChain in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 18 SuperTokens tools available for LangChain

When LangChain connects to SuperTokens through Vinkius, your AI agent gets direct access to every tool listed below — spanning authentication, session-management, rbac, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

assign

Assign role to user on SuperTokens

Assign a role to a user

bulk

Bulk import users on SuperTokens

Bulk import users

create

Create or update role on SuperTokens

Create or update a user role

create

Create or update tenant on SuperTokens

Create or update a tenant

create

Create session on SuperTokens

Create a new session for a user

delete

Delete user metadata on SuperTokens

Delete metadata for a user

get

Get tenant on SuperTokens

Get tenant details

get

Get user on SuperTokens

Get user details by ID

get

Get user metadata on SuperTokens

Get metadata for a user

link

Link accounts on SuperTokens

Link two user accounts together

list

List roles on SuperTokens

List all roles

list

List user roles on SuperTokens

List roles assigned to a user

refresh

Refresh session on SuperTokens

Refresh an existing session

remove

Remove session on SuperTokens

Remove/revoke a session

signin

Signin user on SuperTokens

Sign in a user

signup

Signup user on SuperTokens

Sign up a new user

unlink

Unlink accounts on SuperTokens

Unlink a user account

update

Update user metadata on SuperTokens

Update metadata for a user

Connect SuperTokens to LangChain via MCP

Follow these steps to wire SuperTokens into LangChain. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 18 tools from SuperTokens via MCP

Why Use LangChain with the SuperTokens MCP Server

LangChain provides unique advantages when paired with SuperTokens through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine SuperTokens MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across SuperTokens queries for multi-turn workflows

SuperTokens + LangChain Use Cases

Practical scenarios where LangChain combined with the SuperTokens MCP Server delivers measurable value.

01

RAG with live data: combine SuperTokens tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query SuperTokens, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain SuperTokens tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every SuperTokens tool call, measure latency, and optimize your agent's performance

Example Prompts for SuperTokens in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with SuperTokens immediately.

01

"Get details for user ID 'user-123'."

02

"Assign the 'editor' role to user 'user-456'."

03

"List all available roles in the system."

Troubleshooting SuperTokens MCP Server with LangChain

Common issues when connecting SuperTokens to LangChain through Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

SuperTokens + LangChain FAQ

Common questions about integrating SuperTokens MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

Explore More MCP Servers

View all →