How do I find my Highnote API Key?

Log in to your Highnote dashboard, navigate to **Settings > API**, and you will be able to generate and copy your API key. Make sure to distinguish between Test and Live keys based on your environment.

What environments are supported?

The integration supports both the **Test** (Sandbox) and **Live** (Production) environments. You must specify which one you are connecting to during setup to ensure the correct API endpoints are used.

Can I freeze a card through this integration?

Yes! Use the `update_card_status` tool and set the status to `FROZEN`. This will immediately prevent any new authorizations on that card. You can set it back to `ACTIVE` to unfreeze it.

Is the integration secure for financial data?

Absolutely. The integration uses industry-standard Basic Authentication over HTTPS. Your credentials and financial data are encrypted and stored securely within the Vinkius Cloud infrastructure.

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

Name: Highnote
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 Highnote 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({
        "highnote": {
            "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 Highnote, 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

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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 Highnote MCP Server

Connect your Highnote card platform to any AI agent and take full control of your card issuance, financial accounts, and ledger through natural conversation.

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

What you can do

Account Holder Oversight — List and retrieve details for individuals and businesses holding accounts in your program.
Card Management — List virtual and physical cards, monitor their operational status, and freeze or close them directly from the chat.
Financial Account Monitoring — Access real-time balances and metadata for all your financial ledger accounts.
Transaction Tracking — List and inspect recent spending and processing transactions with detailed merchant metadata.
Ledger Insights — Retrieve individual ledger entries for reconciliation and audit purposes.
Program Visibility — List all available card products and programs configured in your Highnote account.

The Highnote 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 Highnote to LangChain via MCP

Follow these steps to integrate the Highnote 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 Highnote via MCP

Why Use LangChain with the Highnote MCP Server

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

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

Highnote + LangChain Use Cases

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

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

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

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

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

Highnote MCP Tools for LangChain (11)

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

get_api_profile

Retrieve information about the authenticated API user

get_financial_account

Get detailed balance and metadata for a specific financial account

get_payment_card_details

Get detailed information for a specific card

get_transaction_details

Get detailed metadata for a specific transaction

list_account_holders

Use this to find the unique ID for a person or business. List individuals and businesses who hold accounts in Highnote

list_card_products

List the different card programs (e.g., Consumer, Fleet) available in your Highnote account

list_financial_accounts

List all financial accounts and their current balances

list_financial_transactions

List recent spending and processing transactions

list_ledger_entries

Useful for reconciliation. List individual ledger entries for a financial account

list_payment_cards

Monitor card status and expiration details. List virtual and physical cards issued in your program

update_card_status

Valid statuses: ACTIVE, FROZEN, CLOSED. Change the status of a card (e.g., ACTIVE, FROZEN, CLOSED)

Example Prompts for Highnote in LangChain

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

"List all financial accounts and show their current balances."

"Show the last 5 transactions for card ending in 4492."

"Freeze card ID 'card_992' immediately."

Troubleshooting Highnote MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Highnote + LangChain FAQ

Common questions about integrating Highnote 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.