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Sender.net MCP Server for LangChainGive LangChain instant access to 11 tools to Create Campaign, Create Subscriber, Delete Subscriber, and more

Built by Vinkius GDPR 11 Tools Framework

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

asyncio.run(main())
Sender.net
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 Sender.net MCP Server

Connect your Sender.net account to any AI agent and take full control of your email marketing orchestration through natural conversation. Sender.net provides a powerful and affordable platform for managing subscribers, creating automated campaigns, and tracking engagement, and this integration allows you to orchestrate your entire marketing ecosystem without leaving your chat interface.

LangChain's ecosystem of 500+ components combines seamlessly with Sender.net 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

  • Subscriber & Audience Orchestration — List all managed subscribers and retrieve detailed profile metadata, including creating and organizing contacts into groups programmatically.
  • Campaign Performance Intelligence — Retrieve real-time analytics for sent campaigns, including open rates, click-through rates, and subscriber growth via natural language.
  • Group & Segment Control — Manage your subscriber lists and group associations to ensure your targeted communication is always synchronized directly from the AI interface.
  • Transactional Messaging Management — Access account profile metadata and monitor campaign delivery statuses using simple AI commands.
  • Operational Monitoring — Track system activity and monitor audience health to ensure your marketing operations are always optimized.

The Sender.net 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 Sender.net tools available for LangChain

When LangChain connects to Sender.net through Vinkius, your AI agent gets direct access to every tool listed below — spanning sender, email-marketing, newsletter-api, 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_campaign

Create a new email campaign

create_subscriber

Add a new subscriber

delete_subscriber

Remove a subscriber

get_campaign_analytics

Get performance metrics

get_group

Get details for a subscriber group

get_subscriber_details

Get details for a subscriber

get_user_profile

Get your Sender.net profile

list_email_campaigns

List all sent and draft campaigns

list_subscriber_groups

List your contact groups

list_subscribers

Supports filtering by group or status. List your Sender.net subscribers

update_subscriber

Update subscriber information

Connect Sender.net to LangChain via MCP

Follow these steps to wire Sender.net 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 Sender.net via MCP

Why Use LangChain with the Sender.net MCP Server

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

01

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

Sender.net + LangChain Use Cases

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

01

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

02

Autonomous research agents: LangChain agents query Sender.net, synthesize findings, and generate comprehensive research reports

03

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

04

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

Example Prompts for Sender.net in LangChain

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

01

"List all active campaigns in my Sender.net account."

02

"Show me the subscriber analytics with engagement segments and list health metrics."

03

"Create a new email campaign for the Product Updates group announcing our latest feature release."

Troubleshooting Sender.net MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Sender.net + LangChain FAQ

Common questions about integrating Sender.net 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.