3,400+ MCP servers ready to use
Vinkius

Quentn MCP Server for LangChainGive LangChain instant access to 11 tools to Create Contact, Delete Contact, Get Campaign, and more

Built by Vinkius GDPR 11 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Quentn 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 App Connector for LangChain

The Quentn app connector for LangChain is a standout in the Industry Titans category — giving your AI agent 11 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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({
        "quentn": {
            "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 Quentn, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
Quentn
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 Quentn MCP Server

Connect your Quentn account to any AI agent and take full control of your CRM orchestration and marketing automation through natural conversation. Quentn provides a powerful platform for managing customer relationships and complex marketing sequences, and this integration allows you to retrieve contact metadata, trigger campaign sequences, and manage tags (terms) directly from your chat interface.

LangChain's ecosystem of 500+ components combines seamlessly with Quentn through native MCP adapters. Connect 11 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

  • Contact & CRM Orchestration — List, create, and update contacts with detailed profile metadata programmatically to ensure your sales database is always synchronized.
  • Campaign Lifecycle Management — Access and monitor your marketing campaigns and trigger specific sequences for contacts directly from the AI interface.
  • Tag & Segment Control — Manage terms (tags) to maintain a clear overview of your audience segmentation via natural language.
  • Omnichannel Communication — Send automated emails through the Quentn system to ensure consistent customer engagement.
  • Operational Monitoring — Track system activity and manage custom fields to ensure your marketing stack is always optimized using simple AI commands.

The Quentn 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.

All 11 Quentn tools available for LangChain

When LangChain connects to Quentn through Vinkius, your AI agent gets direct access to every tool listed below — spanning crm-automation, email-funnels, gdpr-compliance, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_contact

Create a new contact

delete_contact

Delete a contact

get_campaign

Get campaign details

get_contact

Get contact details by ID

get_tag_details

Get details for a specific tag

list_campaigns

List all campaigns

list_contacts

List all contacts

list_tags

List all tags/terms

list_users

List system users

send_email

Send an email to a contact

update_contact

Update an existing contact

Connect Quentn to LangChain via MCP

Follow these steps to wire Quentn into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 11 tools from Quentn via MCP

Why Use LangChain with the Quentn MCP Server

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

01

The largest ecosystem of integrations, chains, and agents. combine Quentn MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Quentn queries for multi-turn workflows

Quentn + LangChain Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Quentn in LangChain

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

01

"List all contacts tagged as 'VIP' in Quentn."

02

"Show me all contacts who opened my last email campaign but did not click any link."

03

"Create a new contact with tag VIP Customer and add them to the onboarding automation sequence."

Troubleshooting Quentn MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Quentn + LangChain FAQ

Common questions about integrating Quentn MCP Server with LangChain.

01

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.
02

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.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.