Are actions simulated or operating live on real Ledgers?

If you inject your core Project Access Token with full production permissions and leave the `env` string off `sandbox`, yes! It executes heavy Core Banking GraphQL mutations that immediately provision legally compliant EU ledgers behind the scenes.

Can the AI Agent manage physical or virtual credit cards?

Yes. Via `swan_add_virtual_card` and `swan_cancel_card` the LLM has complete programmatic control over debit and spend cards mapped to underlying accounts.

Does the system support sandbox incoming money simulation?

Yes! We expose the `swan_simulate_incoming_transfer` specifically so you can test your programmatic workflows in SandBox by pushing fake money into target ledgers.

Swan MCP Server for LangChain 9 tools — connect in under 2 minutes

Name: Swan
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 9 Tools Framework

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

The Swan MCP Server embeds a complete European Banking-as-a-Service architecture into Vinkius LLMs.

LangChain's ecosystem of 500+ components combines seamlessly with Swan through native MCP adapters. Connect 9 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

Automated Root Provisioning — Instantly spin up local branch operations allocating FRA or ESP IBAN formats through swan_create_account.
Card Administration — Ask the agent to generate custom virtual Mastercards assigned exclusively to distinct contractors utilizing swan_add_virtual_card.
Direct SEPA Execution — Move exact funds safely parsing external creditor data natively through swan_create_sepa_transfer directly across European networks.

The Swan MCP Server exposes 9 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 Swan to LangChain via MCP

Follow these steps to integrate the Swan 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 9 tools from Swan via MCP

Why Use LangChain with the Swan MCP Server

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

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

Swan + LangChain Use Cases

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

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

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

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

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

Swan MCP Tools for LangChain (9)

These 9 tools become available when you connect Swan to LangChain via MCP:

swan_add_virtual_card

Provisions a robust Mastercard Virtual Debit

swan_cancel_card

Permanently cancel a specific corporate card

swan_create_account

Requires an existing AccountHolderId. Dynamically provision a European Account under your ledger

swan_create_sepa_transfer

Initiate a standard European SEPA Credit Transfer

swan_get_accounts

List all operational Swan Bank Accounts/IBANs

swan_get_project_info

Fetch overarching details about your connected Swan Project Node

swan_get_transactions

Retrieve the ledger history for a specific Account

swan_list_cards

List all physical and virtual cards

swan_simulate_incoming_transfer

Sandbox Only - Inject fake money

Example Prompts for Swan in LangChain

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

"Retrieve my core project identifier and map the legal entity ID."

"Launch a brand new sub-account in France. Bind it to the root entity targeting EUR processing."

"Sweep the ledger of Account X123 and list the latest 5 transactions."

Troubleshooting Swan MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Swan + LangChain FAQ

Common questions about integrating Swan 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.