Momence MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Momence 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({
"momence": {
"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 Momence, 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 Momence MCP Server
Connect your Momence studio to any AI agent and manage your fitness business through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Momence 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
- Sessions — View upcoming classes with teacher, capacity, waitlist, and streaming links
- Members — Search member database, view credits, tags, and attendance history
- Teachers — List instructors with bios, specialties, and class assignments
- Memberships — Browse plans: unlimited, class packs, intro offers, trials
- Bookings — Track who booked which session, check-in and waitlist status
- Locations — Manage multi-location studios with rooms and timezone
- Products — View retail items, digital content, and merchandise
The Momence 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 Momence to LangChain via MCP
Follow these steps to integrate the Momence 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 Momence via MCP
Why Use LangChain with the Momence MCP Server
LangChain provides unique advantages when paired with Momence through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Momence 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 Momence queries for multi-turn workflows
Momence + LangChain Use Cases
Practical scenarios where LangChain combined with the Momence MCP Server delivers measurable value.
RAG with live data: combine Momence tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Momence, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Momence tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Momence tool call, measure latency, and optimize your agent's performance
Momence MCP Tools for LangChain (10)
These 10 tools become available when you connect Momence to LangChain via MCP:
get_member
Get member profile
get_session
Get session details
list_bookings
List session bookings
list_locations
List studio locations
list_memberships
List membership plans
list_products
List products/retail
list_session_types
with description, default duration, and default teacher. List class types
list_sessions
Filter by date range. List scheduled sessions
list_teachers
List teachers/instructors
search_members
Returns profile, active memberships, credits, and visit history. Search studio members
Example Prompts for Momence in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Momence immediately.
"How full are tomorrow's yoga classes?"
"List the upcoming classes for instructor Sarah."
"How many active members are on the Unlimited Monthly plan?"
Troubleshooting Momence MCP Server with LangChain
Common issues when connecting Momence to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersMomence + LangChain FAQ
Common questions about integrating Momence 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 Momence 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 Momence to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.