Courier MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Courier 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 MCP SERVER
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({
"courier": {
"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 Courier, 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 Courier MCP Server
Integrate Courier, the smart notification infrastructure, directly into your AI workflow. Design, orchestrate, and send messages across email, SMS, push, and chat apps using natural language.
LangChain's ecosystem of 500+ components combines seamlessly with Courier 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
- Send Notifications — Trigger complex notification workflows to any recipient via the Send API.
- Message Monitoring — List sent messages and track their real-time delivery status (sent, delivered, opened).
- Template Management — Browse available notification templates and custom brands.
- Audience & User Insights — Manage subscription lists and retrieve user profiles.
The Courier 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 Courier to LangChain via MCP
Follow these steps to integrate the Courier 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 Courier via MCP
Why Use LangChain with the Courier MCP Server
LangChain provides unique advantages when paired with Courier through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Courier 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 Courier queries for multi-turn workflows
Courier + LangChain Use Cases
Practical scenarios where LangChain combined with the Courier MCP Server delivers measurable value.
RAG with live data: combine Courier tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Courier, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Courier tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Courier tool call, measure latency, and optimize your agent's performance
Courier MCP Tools for LangChain (10)
These 10 tools become available when you connect Courier to LangChain via MCP:
get_message_details
Touches delivery logs, provider responses, and rendering metadata boundary. Get details for a specific message by ID
get_message_history
Resolves event types (SENT, DELIVERED, etc.) and detailed provider logs. Get the delivery history logs for a message
get_user_profile
Resolves contact details (email, phone) and channel-specific delivery preferences. Get the profile data for a specific user
list_audiences
Resolves audience IDs, names, and filter criteria used for segmentation. List saved audiences for targeted notifications
list_brands
Resolves brand names, colors, and logo settings used for white-labeling notifications. List custom brands configured in Courier
list_messages
Resolves message IDs, recipient identifiers, status (SENT, DELIVERED, OPENED, CLICKED), and timestamps. List sent messages and their current status
list_subscription_lists
Resolves list IDs, names, and subscriber counts. List subscription lists for managing recipients
list_templates
Resolves template names, IDs, and supported channels. List available notification templates
list_users
Resolves user IDs, roles, and account association details. List users registered in the Courier workspace
send_notification
Touches recipient profile, template engine, and multi-channel provider boundaries. Send a notification to a recipient
Example Prompts for Courier in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Courier immediately.
"Check the delivery status of the last message sent to 'user@example.com'."
"Send a 'Welcome' notification to the new user with ID 'user_123'."
"List all notification templates available in my account."
Troubleshooting Courier MCP Server with LangChain
Common issues when connecting Courier to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersCourier + LangChain FAQ
Common questions about integrating Courier 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 Courier 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 Courier to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.