Loops MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Loops through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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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({
"loops": {
"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 Loops, 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 Loops MCP Server
Loops is a modern email marketing and transactional email platform designed for startups and growing businesses. It provides powerful automation for email journeys, audience segmentation, contact management, and detailed analytics. This MCP server enables AI agents to manage contacts, mailing lists, trigger events for automated journeys, send transactional emails, and check suppression statuses — all through natural language commands.
LangChain's ecosystem of 500+ components combines seamlessly with Loops 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.
Key capabilities:
- Search, create, update, and delete contacts
- Manage mailing lists
- Trigger email journeys with events
- Send transactional emails programmatically
- Check email suppression status
- View sent transactional email history
The Loops 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 Loops to LangChain via MCP
Follow these steps to integrate the Loops 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 Loops via MCP
Why Use LangChain with the Loops MCP Server
LangChain provides unique advantages when paired with Loops through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Loops 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 Loops queries for multi-turn workflows
Loops + LangChain Use Cases
Practical scenarios where LangChain combined with the Loops MCP Server delivers measurable value.
RAG with live data: combine Loops tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Loops, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Loops tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Loops tool call, measure latency, and optimize your agent's performance
Loops MCP Tools for LangChain (10)
These 10 tools become available when you connect Loops to LangChain via MCP:
create_contact
Requires an email address. Optionally accepts firstName, lastName, and userGroup. Create a new contact in Loops
delete_contact
This action cannot be undone. Delete a contact from Loops by ID
find_contact
Returns the contact details if found. Find a contact in Loops by email address
get_contact_suppression
Suppressed emails will not receive emails. Returns the suppression status for the given email. Check if an email address is suppressed in Loops
list_mailing_lists
Use this to discover available lists for subscribing contacts. List all mailing lists in Loops
list_transactional_emails
Optionally accepts a limit parameter to control the number of results returned. List recently sent transactional emails from Loops
send_event
Requires an eventName. Optionally accepts email and/or userId to identify the recipient. Send an event to trigger email journeys in Loops
send_transactional_email
Requires the transactionalId. Optionally accepts email and dataVariables (as JSON string) for template variables. Send a transactional email via Loops
test_api_key
Returns success/failure status. Test if the Loops API key is valid and working
update_contact
Requires the contact ID. Accepts any fields to update such as firstName, lastName, email, userGroup, etc. Update an existing contact in Loops by ID
Example Prompts for Loops in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Loops immediately.
"Find the contact with email user@example.com in Loops"
"Create a new contact in Loops with email newuser@example.com, first name John, and last name Doe"
"List all mailing lists in my Loops account"
"Send a transactional email with template txn_123 to customer@example.com"
Troubleshooting Loops MCP Server with LangChain
Common issues when connecting Loops to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersLoops + LangChain FAQ
Common questions about integrating Loops 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 Loops 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 Loops to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.