Where do I find my Quaderno API Key and URL?

Log in to your Quaderno account. Your **API URL** is simply your domain up top in the browser bar (e.g., `https://mycompany.quadernoapp.com`). To get the **API Key**, navigate to **Settings** > **API Keys** (or Developers), and copy your private key. Do not share this key as it carries full access. Paste both credentials below.

Can it calculate exact taxes dynamically before a sale?

Yes! Use the `calculate_taxes` tool and just provide the AI with a country code, postal code, and base amount. Quaderno's world-class engine evaluates real-time location-based tax nuances (VAT, GST) and returns the exact fraction needed.

Can I draft custom test invoices natively in chat?

Absolutely. You can use `create_transaction`. Instruct your agent to format a JSON array with products and amounts, linking to a specific `contact_id`. The server submits this array to Quaderno and records the fully realized transaction safely.

Will deleting a contact via the AI remove them permanently?

Yes. The `delete_contact` operation relies heavily on standard destructive API instructions. Running this means the contact is gone entirely from the Quaderno dashboard. Always review deletion queries cautiously before approving execution.

Quaderno MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Quaderno
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Quaderno 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({
        "quaderno": {
            "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 Quaderno, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* 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 Quaderno MCP Server

Connect your Quaderno account to any AI agent and bring powerful tax compliance, invoicing, and customer management capabilities directly into your automated workflows.

LangChain's ecosystem of 500+ components combines seamlessly with Quaderno through native MCP adapters. Connect 10 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

Tax Calculations on the Fly — Instantly determine the accurate sales tax, VAT, or GST based on the customer's region and amount before finalizing sales logic
Invoice Management — Search and retrieve generated invoices, audit billing records, and verify transactions perfectly formatted via intelligent prompts
Generate Transactions — Transact and issue invoices seamlessly by sending a simple JSON array of itemized products and line item prices
Full Contact CRM — Map your users fully by creating, modifying, retrieving, and safely deleting user contacts and billing profiles natively

The Quaderno MCP Server exposes 10 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 Quaderno to LangChain via MCP

Follow these steps to integrate the Quaderno 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 10 tools from Quaderno via MCP

Why Use LangChain with the Quaderno MCP Server

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

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

Quaderno + LangChain Use Cases

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

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

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

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

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

Quaderno MCP Tools for LangChain (10)

These 10 tools become available when you connect Quaderno to LangChain via MCP:

calculate_taxes

Calculates applicable taxes for a potential sale

create_contact

Specify email, first name, and last name. Creates a new contact in Quaderno

create_transaction

Provide the contact ID and a JSON array of items. Records a new transaction and issues an invoice

delete_contact

This action is irreversible. Deletes a contact from Quaderno

get_contact

Retrieves details for a specific contact

get_invoice

Retrieves details for a specific invoice

list_contacts

Lists all contacts (customers) in the Quaderno account

list_invoices

Lists all issued invoices

list_transactions

Lists all recorded transactions

update_contact

Provide a JSON payload with the changes. Updates an existing contact

Example Prompts for Quaderno in LangChain

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

"Calculate the taxes for a $150 plan sold to a user in Berlin, Germany (Postal Code 10115)."

"Fetch the billing details and history for contact ID #9822."

"Update contact #9822 to change its first name to 'Acorn Group Inc'."

Troubleshooting Quaderno MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Quaderno + LangChain FAQ

Common questions about integrating Quaderno 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.