How do I find my Mambu API Key?

Log in to your Mambu administration panel, go to Administration > Access > API Keys. There you can generate or copy your existing API key.

What is the subdomain?

The subdomain is the first part of your Mambu URL. For example, if your URL is 'vinkius.mambu.com', your subdomain is 'vinkius'.

Mambu MCP Server for LangChain 11 tools — connect in under 2 minutes

Name: Mambu
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 11 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Mambu through the 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({
        "mambu": {
            "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 Mambu, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 Mambu MCP Server

The Mambu MCP server allows you to interact with your Mambu tenant. You can list and get details for clients, loan accounts, deposit accounts, transactions, tasks, activities, and communications. This integration uses the Mambu v2 REST API to provide a seamless experience for managing your banking operations. Your token is encrypted at rest and injected securely at runtime.

LangChain's ecosystem of 500+ components combines seamlessly with Mambu through native MCP adapters. Connect 11 tools via the 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.

The Mambu MCP Server exposes 11 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 Mambu to LangChain via MCP

Follow these steps to integrate the Mambu 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 11 tools from Mambu via MCP

Why Use LangChain with the Mambu MCP Server

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

The largest ecosystem of integrations, chains, and agents — combine Mambu 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 Mambu queries for multi-turn workflows

Mambu + LangChain Use Cases

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

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

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

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

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

Mambu MCP Tools for LangChain (11)

These 11 tools become available when you connect Mambu to LangChain via MCP:

get_client

Get details for a specific Mambu client

get_deposit_account

Get details for a specific Mambu deposit account

get_loan_account

Get details for a specific Mambu loan account

get_task

Get details for a specific Mambu task

list_activities

List Mambu activities

list_clients

List Mambu clients

list_communications

List Mambu communications

list_deposit_accounts

List Mambu deposit accounts

list_loan_accounts

List Mambu loan accounts

list_tasks

List Mambu tasks

list_transactions

List Mambu transactions

Example Prompts for Mambu in LangChain

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

"List all clients in Mambu"

"Show details for client with ID 12345"

"List my tasks in Mambu"

Troubleshooting Mambu MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Mambu + LangChain FAQ

Common questions about integrating Mambu 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.