eSputnik MCP Server for LangChainGive LangChain instant access to 12 tools to Attach To Group, Create Contact, Detach From Group, and more
LangChain is the leading Python framework for composable LLM applications. Connect eSputnik 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 eSputnik app connector for LangChain is a standout in the Marketing category — giving your AI agent 12 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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({
"esputnik": {
"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 eSputnik, 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 eSputnik MCP Server
The eSputnik MCP server allows your AI agent to orchestrate marketing campaigns across Email, SMS, Web Push, and Mobile Push. Send messages, retrieve contact lists, and manage omnichannel workflows seamlessly.
LangChain's ecosystem of 500+ components combines seamlessly with eSputnik through native MCP adapters. Connect 12 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.
The eSputnik MCP Server exposes 12 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 12 eSputnik tools available for LangChain
When LangChain connects to eSputnik through Vinkius, your AI agent gets direct access to every tool listed below — spanning esputnik, email, sms, 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.
Add contacts to a specific group
Create a new contact in eSputnik
Remove contacts from a group
Retrieve account and organization metadata
Retrieve details for a specific contact
Check the delivery status of a sent message
List all contacts in eSputnik
List all contact groups/segments
List unsubscribed email addresses
Search for contacts by email or phone
Trigger an omnichannel message send
Generate a system event to trigger workflows
Connect eSputnik to LangChain via MCP
Follow these steps to wire eSputnik into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the eSputnik MCP Server
LangChain provides unique advantages when paired with eSputnik through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine eSputnik 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 eSputnik queries for multi-turn workflows
eSputnik + LangChain Use Cases
Practical scenarios where LangChain combined with the eSputnik MCP Server delivers measurable value.
RAG with live data: combine eSputnik tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query eSputnik, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain eSputnik tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every eSputnik tool call, measure latency, and optimize your agent's performance
Example Prompts for eSputnik in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with eSputnik immediately.
"List all my contact groups in eSputnik."
"Send an SMS saying 'Your order has shipped!' to +123456789."
"Add 'john@example.com' to the 'VIP Customers' list."
Troubleshooting eSputnik MCP Server with LangChain
Common issues when connecting eSputnik to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adapterseSputnik + LangChain FAQ
Common questions about integrating eSputnik 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.