Modulr requires complex timestamped HMAC API Signatures, how does the prompt handle that?

We handle that completely in the background Engine! The Vinkius runtime grabs your static API Secret from configurations once. Then, every time the Language Model triggers a payment, our Node.js runtime creates random cryptographic hex Nonces, aligns current UTC Date limits, hashes the combination uniquely via SHA-256 and packs it into the underlying header dynamically natively.

Can the Agent generate new SEPA/UK Accounts?

Yes, using `modulr_create_account`, you can spawn multiple isolated UK GBP ledgers natively linked to customers.

Are cross-border Faster Payments supported natively?

Absolutely. You can inject external sorts codes inside the `modulr_create_payment` orchestrations delivering funds transparently via clearing houses.

Modulr MCP Server for LangChain 7 tools — connect in under 2 minutes

Name: Modulr
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 7 Tools Framework

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

The Modulr MCP Server wraps incredibly defensive digital signatures (HMAC SHA-256) autonomously underneath a native Language Model Chat interface. Meaning, your AI has programmatic limits to fire secure European and British payment rails on command natively.

LangChain's ecosystem of 500+ components combines seamlessly with Modulr through native MCP adapters. Connect 7 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.

Core Functionality

Create Modulr Customers/Accounts — Manage deeply nested multi-layered B2B structures. Automatically provision Sort-Code ledgers via modulr_create_account.
Payment Initiation — Run automated payroll or contractor compensation logic utilizing direct clearing paths mapping via modulr_create_payment.
Algorithmic Tracing — Check real-time payment states checking failures or settlements organically utilizing modulr_list_payments.

Use Cases

Lending Startups — Direct integration validating funds exactly when needed.
Payment Reconciliations — Have the Agent review your physical transactional ledger.

The Modulr MCP Server exposes 7 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 Modulr to LangChain via MCP

Follow these steps to integrate the Modulr 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 7 tools from Modulr via MCP

Why Use LangChain with the Modulr MCP Server

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

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

Modulr + LangChain Use Cases

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

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

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

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

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

Modulr MCP Tools for LangChain (7)

These 7 tools become available when you connect Modulr to LangChain via MCP:

modulr_create_account

g. GBP or EUR). Instantiate a UK/EU Account under a specific Customer

modulr_create_beneficiary

, or IBAN. Map an external Recipient

modulr_create_payment

Trigger an outgoing Faster Payment or SEPA payout

modulr_get_accounts

List all live Accounts and mapped liquidity

modulr_get_customers

List underlying legal customers/entities inside Modulr

modulr_get_transactions

Audit transaction histories on a specific Account

modulr_list_payments

Check the status of massive payment arrays

Example Prompts for Modulr in LangChain

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

"Check our main UK sub-account. View the history array mapped onto it to find pending activity."

"Initialize a payment stream. Register a Beneficiary named 'DevTeam' pointing to target Sort Code 123456 Acct 98765432. Send £5,000 from Account 'A110' natively."

"Scan our Modulr operational Customers and list the active instances returning metadata boundaries."

Troubleshooting Modulr MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Modulr + LangChain FAQ

Common questions about integrating Modulr 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.