Can I test money flows safely without losing real funds?

Absolutely. Increase has a top-tier sandbox environment. In your MCP settings, pass a Sandbox API Key (starting with `sk_test_`) and optionally set the environment to 'sandbox'. We even implemented literal tool overrides like `increase_simulate_inbound_ach` which are intentionally restricted exclusively to simulating inbound events on your test environment.

Does adding a new account via the Agent require paperwork?

No! Assuming your global LLC has already passed initial onboarding and your Entity object handles compliance, any subsequent programmatic calls to `increase_create_account` yield a fully compliant sub-ledger and associated numbers instantaneously contextually within the UI chat responses.

What is the difference between ACH and Wire transfer arrays here?

ACH acts through clearing houses taking normally 1-3 business days suited perfectly for non-urgent vendor mass payouts (`create_ach`). Wire transfers (`create_wire`) tie directly to Fedwire routing logic hitting banks internally within minutes - often bearing a slight static fee. Dictate which the bot should invoke based on liquidity needs.

How can I trace a specific payment?

We've added `increase_list_transactions` to handle historical booked transfers strictly by ID limits, exposing whether money cleared Fed limits safely.

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

Name: Increase
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 Increase 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({
        "increase": {
            "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 Increase, 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 Increase MCP Server

The Increase MCP Server connects AI to a physical, fully compliant commercial US bank built explicitly top-down for programmatic transactions.

LangChain's ecosystem of 500+ components combines seamlessly with Increase 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.

What you can do

Endless Provisioning — Instantly generate new live bank accounts increase_create_account acting as sub-ledgers, enabling separate balances.
Open Payment Rails — Need to inject funds into a supplier directly using native American payment streams? Use increase_create_ach or sweep high-value overnight increase_create_wire securely.
Simulation Environment — Use Sandbox arrays to trigger simulated money hits increase_simulate_inbound_ach checking if an external agent script validates receiving deposits before going to production.

The Increase 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 Increase to LangChain via MCP

Follow these steps to integrate the Increase 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 Increase via MCP

Why Use LangChain with the Increase MCP Server

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

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

Increase + LangChain Use Cases

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

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

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

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

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

Increase MCP Tools for LangChain (12)

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

increase_create_account

Spin up a new Bank Account programmatically

increase_create_ach

Push an outbound ACH transfer to any US Bank

increase_create_card

Issue a physical/virtual debit card attached to an account

increase_create_routing_number

Generate new ABA routing & account number data

increase_create_wire

Send a same-day US Wire transfer

increase_get_balance

Fetch realtime ledger balance for a specific account

increase_list_accounts

List all sub-accounts under your charter

increase_list_cards

Sweep the active array of issued Cards

increase_list_transactions

Financial history extraction (Booked)

increase_list_transfers

Audit outbound transfers

increase_simulate_inbound_ach

Simulate receiving an ACH inbound (SANDBOX ONLY)

increase_simulate_inbound_wire

Simulate receiving a Wire inbound (SANDBOX ONLY)

Example Prompts for Increase in LangChain

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

"Use our main test routing sandbox mechanism to simulate inbound an external payload of $1000 into Account ID 'acc_1234'."

"Audit our entire open accounts layout right now."

"Spin up a new fresh physical corporate banking account dedicated uniquely to 'Server Spends'. Send the Routing number to me."

Troubleshooting Increase MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Increase + LangChain FAQ

Common questions about integrating Increase 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.