sevDesk MCP Server for LangChain 15 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect sevDesk through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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({
"sevdesk": {
"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 sevDesk, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 sevDesk MCP Server
Grant your conversational AI (like Claude or Cursor) the power of a dedicated German accounting clerk. The sevDesk MCP transforms your LLM into a sophisticated financial nexus capable of creating invoices, querying past-due credit notes, recording vouchers, and tracking your CRM endpoints dynamically. Stop wrestling with browser-based accounting dashboards and let your AI manage your bookkeeping automatically.
LangChain's ecosystem of 500+ components combines seamlessly with sevDesk through native MCP adapters. Connect 15 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
- Client & Supplier CRM Mastery — Read the entire client database via
list_contacts, retrieve detailed metadata for specific IDs (get_contact), or seamlessly register brand new vendors viacreate_contact - Autonomous Invoicing & Orders — Fetch paginated ledger lists using
list_invoicesorlist_orders, and delve deep into line items, calculated taxes, and due statuses directly usingget_invoiceandget_order - Inventory & Service Architecture — Monitor available billable components via
list_parts, inspect standard pricing, and introduce novel catalog options autonomously viacreate_part - Accounting Governance — Keep strict tabs on your chart of accounts with
list_accounting_typeswhile verifying associated business inlets securely usinglist_bank_accounts - Voucher & Credit Auditing — Consolidate physical receipts through
list_vouchersand trace structural adjustments flawlessly by scanninglist_credit_notes
The sevDesk MCP Server exposes 15 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 sevDesk to LangChain via MCP
Follow these steps to integrate the sevDesk 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 15 tools from sevDesk via MCP
Why Use LangChain with the sevDesk MCP Server
LangChain provides unique advantages when paired with sevDesk through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine sevDesk 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 sevDesk queries for multi-turn workflows
sevDesk + LangChain Use Cases
Practical scenarios where LangChain combined with the sevDesk MCP Server delivers measurable value.
RAG with live data: combine sevDesk tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query sevDesk, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain sevDesk tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every sevDesk tool call, measure latency, and optimize your agent's performance
sevDesk MCP Tools for LangChain (15)
These 15 tools become available when you connect sevDesk to LangChain via MCP:
create_contact
Category 3 for customers, 4 for suppliers. Creates a new contact (customer or supplier) in sevDesk
create_part
Creates a new part or service in the catalog
get_contact
Retrieves details for a specific contact
get_credit_note
Retrieves details for a specific credit note
get_invoice
Retrieves details for a specific invoice, including line items and tax
get_order
Retrieves details for a specific order
get_part
Retrieves details for a specific part
list_accounting_types
Lists all accounting types (Chart of Accounts)
list_bank_accounts
Lists company bank accounts
list_contacts
Lists all contacts (customers, suppliers) in sevDesk
list_credit_notes
Lists all credit notes
list_invoices
Lists all invoices with embedded contact data
list_orders
Lists all sales orders
list_parts
Lists all parts (products and services) in the catalog
list_vouchers
Lists all vouchers (incoming/outgoing receipts)
Example Prompts for sevDesk in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with sevDesk immediately.
"Extract the details of invoice #18742 and summarize its line items alongside the associated contact name."
"List all currently existing bank accounts natively integrated using the core config."
Troubleshooting sevDesk MCP Server with LangChain
Common issues when connecting sevDesk to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adapterssevDesk + LangChain FAQ
Common questions about integrating sevDesk MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect sevDesk with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect sevDesk to LangChain
Get your token, paste the configuration, and start using 15 tools in under 2 minutes. No API key management needed.