How do I get my Client ID and API Key for Frontegg?

Log in to the Frontegg Portal, select your workspace/environment, go to 'Environment Settings' > 'API Keys', and create a Vendor token to get your Client ID and API Key.

Does this support multi-tenant management?

Yes! The agent can list, create, and delete individual tenants (customer accounts) within your environment using the 'list_tenants' and 'create_tenant' tools.

Can I search for a user across all tenants?

Yes, use the 'list_users' tool and provide an exact 'email' parameter. The agent will search across all tenants in the environment to find the user profile.

Is it possible to view role permissions?

You can use the 'list_system_roles' to view all roles and the 'list_permissions' tool to see the granular permissions available for assignment.

Frontegg MCP Server for LangChain 12 tools — connect in under 2 minutes

Name: Frontegg
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 12 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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({
        "frontegg": {
            "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 Frontegg, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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 Frontegg MCP Server

Connect your Frontegg environment to any AI agent to automate your B2B SaaS identity management through the Model Context Protocol (MCP). Frontegg is a powerful user management and authentication platform designed specifically for modern SaaS applications. This MCP server enables you to manage multi-tenant architectures, provision new users, and audit security configurations directly through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Frontegg through native MCP adapters. Connect 12 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.

Key Features

Tenant Orchestration — List all customer accounts (tenants), retrieve their configuration details, and programmatically create or delete tenants.
User Provisioning — Access your global user database, fetch detailed profiles across tenants, and instantly invite or remove users.
Role & Permission Discovery — List all system roles and granular permissions to audit your security and access control models.
M2M Token Management — Retrieve Machine-to-Machine tokens for specific tenants to simplify backend integrations.
Real-time Synchronization — Keep your identity and access management operations accessible to your AI assistant without leaving your primary workspace.
Secure Environment Access — Authenticate securely using Vendor Client ID and API Keys to perform administrative operations safely.

The Frontegg MCP Server exposes 12 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Frontegg to LangChain via MCP

Follow these steps to integrate the Frontegg MCP Server with LangChain.

Install dependencies

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

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 12 tools from Frontegg via MCP

Why Use LangChain with the Frontegg MCP Server

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

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

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

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

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

Frontegg + LangChain Use Cases

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

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

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

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

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

Frontegg MCP Tools for LangChain (12)

These 12 tools become available when you connect Frontegg to LangChain via MCP:

check_environment_status

Verify API connection

create_tenant

Create a new tenant

create_user

Provision a user

delete_tenant

Delete a tenant

delete_user

Remove a user

get_tenant_details

Get tenant metadata

get_user_details

Get user metadata

list_m2m_tokens

List machine tokens

list_permissions

List granular permissions

list_system_roles

g. Admin, Read-Only) available for assignment. List roles

list_tenants

List all tenants/accounts

list_users

List users globally

Example Prompts for Frontegg in LangChain

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

"List the first 10 tenants in our Frontegg environment."

"Find the user details for 'jane@example.com'."

"Create a new tenant named 'Stark Industries'."

Troubleshooting Frontegg MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Frontegg + LangChain FAQ

Common questions about integrating Frontegg MCP Server with LangChain.

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.

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.