Can I initiate a payout to a vendor's bank account?

Yes! Use the `inter_bank_transfer` or `intra_bank_transfer` action, providing the amount, currency, beneficiary account, and bank code. Your agent will trigger the Brankas Disburse API.

How do I check the status of a customer's direct payment?

Simply ask the agent to `get_transaction` and provide the Transaction ID. It will retrieve the latest status from Brankas (e.g., SUCCESS, FAILED, PENDING).

Does the integration allow fetching connected bank account balances?

Yes. If you have active user consents configured, use the `get_balance` tool to retrieve real-time available balances across the connected accounts.

Brankas MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Brankas
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Brankas 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({
        "brankas": {
            "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 Brankas, 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 Brankas MCP Server

Connect your Brankas Open Finance account to any AI agent and orchestrate your payments, payouts, and financial data workflows across Southeast Asia through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Brankas through native MCP adapters. Connect 8 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

Direct Payments (Money-in) — Initiate checkout sessions to accept instant account-to-account payments and track transaction statuses.
Disbursements (Money-out) — Send payouts automatically through inter-bank or intra-bank transfers and monitor their progress.
Data Aggregation — Retrieve real-time bank account balances, transaction history (statements), and identity data from consented users.

The Brankas MCP Server exposes 8 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 Brankas to LangChain via MCP

Follow these steps to integrate the Brankas 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 8 tools from Brankas via MCP

Why Use LangChain with the Brankas MCP Server

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

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

Brankas + LangChain Use Cases

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

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

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

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

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

Brankas MCP Tools for LangChain (8)

These 8 tools become available when you connect Brankas to LangChain via MCP:

create_checkout

Create a new Direct payment checkout session

get_balance

Retrieve linked bank account balances

get_identities

Retrieve linked identity data

get_statement

Retrieve linked bank statement data

get_transaction

Get status of a Direct payment transaction

get_transfer_status

Get status of a Disburse transfer

inter_bank_transfer

Initiate an inter-bank disbursement (payout)

intra_bank_transfer

Initiate an intra-bank disbursement (payout)

Example Prompts for Brankas in LangChain

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

"Create a checkout session for 500 PHP."

"Check the status of transfer trf_99283."

"Retrieve the latest bank statement data."

Troubleshooting Brankas MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Brankas + LangChain FAQ

Common questions about integrating Brankas 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.