How to Use the Increase MCP in LangChain

Build automated financial pipelines directly into your LangChain agents with the Increase MCP Server.

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Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Increase MCP to LangChain

Create your Vinkius account to connect Increase to LangChain and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Increase with LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Chain financial operations with LangChain

Feed account data directly into your agent reasoning loops. Use `increase_list_transactions` to pull ledger entries and pass that output into your next processing step without manual intervention. Your agent manages the entire chain. It moves from checking balances with `increase_get_balance` to executing payments via `increase_create_ach` based on the logic you define in your graph.

Programmatic banking for your LangChain agent

Stop waiting on banking portals for routine tasks. Use `increase_create_account` and `increase_create_routing_number` to spin up infrastructure on demand within your code. Everything happens through standard tool calls. Your agent handles the heavy lifting while you focus on the business logic of your financial workflows.

Audit your financial chains in real-time

Track every tool invocation using standard observability patterns. When your agent calls `increase_create_wire`, the input and output are captured immediately for your audit trail. This visibility ensures you know exactly why a transaction occurred. You get a clear log of every decision your agent makes regarding your funds.

Setup guide

Set up Increase MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Increase tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "increase-mcp": {
        "transport": "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,
    )
    result = await agent.ainvoke({
        "messages": "List recent Increase transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Increase. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Real-time monitoring

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

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place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Increase MCP in LangChain

You increase throughput by chaining asynchronous tool calls. Build a graph that handles multiple `increase_create_ach` requests in parallel to avoid bottlenecks.

Yes, it provides granular event data. You can trace every step of your financial logic inside the client to see exactly how you increase the precision of your ledger reconciliations.

You remove manual steps by automating account management. By letting your agent handle routine bank calls, you significantly reduce the latency of your financial processes.

Your API credentials stay local to your environment. The MCP server treats your sensitive banking records as ephemeral data, never storing it beyond the active session.

The tool returns an error object containing the reason for the failure. You can write your agent logic to catch these responses and trigger a retry or alert.

Use it with your favorite AI tools

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