How do I get a TeamUp API key?

Visit goteamup.com/developers to request developer API access. You'll receive an API key that must be passed in the X-Api-Key header with each request.

TeamUp MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: TeamUp
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect TeamUp through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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({
        "teamup": {
            "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 TeamUp, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

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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 TeamUp MCP Server

Connect your TeamUp studio to any AI agent and manage your fitness business through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with TeamUp 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

Events — View scheduled classes and events with coaches, venues, and capacity
Event Types — Browse class formats: CrossFit, Yoga, HIIT, Open Gym
Registrations — Track who booked which class and check-in status
Customers — Search members, view profiles, and track attendance
Memberships — Browse all plans with pricing and billing frequency
Coaches — List trainers with certifications and class assignments
Venues — Manage training locations and room configurations
Payments — Track revenue from memberships, drop-ins, and packages

The TeamUp 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 TeamUp to LangChain via MCP

Follow these steps to integrate the TeamUp 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 TeamUp via MCP

Why Use LangChain with the TeamUp MCP Server

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

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

TeamUp + LangChain Use Cases

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

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

Autonomous research agents: LangChain agents query TeamUp, synthesize findings, and generate comprehensive research reports

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

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

TeamUp MCP Tools for LangChain (10)

These 10 tools become available when you connect TeamUp to LangChain via MCP:

get_customer

Get member profile

get_event

Get event details

list_coaches

List coaches and trainers

list_event_types

Includes description, default duration, and default coach. List class/event types

list_events

Filter by date range. List scheduled classes/events

list_memberships

List membership plans

list_payments

Includes amount, method, and member. List payments and revenue

list_registrations

Shows check-in status, waitlist position, and booking time. List event registrations

list_venues

Includes address and capacity. List training venues

search_customers

Returns profile, active membership, visit count, and account balance. Search members

Example Prompts for TeamUp in LangChain

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

"What's this week's class schedule?"

"Check the availability of exactly 'Conference Room A' for tomorrow afternoon."

"Schedule a new event 'Q1 Review Review' in the Executive Calendar for next Monday at 10 AM."

Troubleshooting TeamUp MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

TeamUp + LangChain FAQ

Common questions about integrating TeamUp MCP Server with LangChain.

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.

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.