Wellhub (formerly Gympass) is the world's largest corporate wellness platform, providing employees access to 50,000+ gyms, studios, and wellness apps in 11 countries. Companies subscribe to provide fitness benefits, and partner gyms receive Wellhub members.

Wellhub MCP Server for LlamaIndex 8 tools — connect in under 2 minutes

Name: Wellhub
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Wellhub as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Wellhub. "
            "You have 8 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Wellhub?"
    )
    print(response)

asyncio.run(main())

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About Wellhub MCP Server

Connect your Wellhub (formerly Gympass) account to any AI agent and manage your corporate wellness program through natural conversation.

LlamaIndex agents combine Wellhub tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Eligibility — Check employee eligibility, manage enrollment, and verify plan access
Check-ins — Track gym visits, validate QR codes, and monitor utilization
Bookings — View class reservations made through the Wellhub app
Classes — List published classes visible to corporate members
Locations — Manage partner gym and studio locations
Partner Profile — Access business details, amenities, and network tier

The Wellhub MCP Server exposes 8 tools through the Vinkius. Connect it to LlamaIndex 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 Wellhub to LlamaIndex via MCP

Follow these steps to integrate the Wellhub MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 8 tools from Wellhub

Why Use LlamaIndex with the Wellhub MCP Server

LlamaIndex provides unique advantages when paired with Wellhub through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Wellhub tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Wellhub tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Wellhub, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Wellhub tools were called, what data was returned, and how it influenced the final answer

Wellhub + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Wellhub MCP Server delivers measurable value.

Hybrid search: combine Wellhub real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Wellhub to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Wellhub for fresh data

Analytical workflows: chain Wellhub queries with LlamaIndex's data connectors to build multi-source analytical reports

Wellhub MCP Tools for LlamaIndex (8)

These 8 tools become available when you connect Wellhub to LlamaIndex via MCP:

check_eligibility

Returns plan tier and access permissions. Check employee eligibility

get_partner_info

Get partner profile

list_bookings

Shows class name, time, member name, and booking status. List class bookings

list_check_ins

Shows gym name, date, time, and plan used. Essential for utilization reporting. List gym check-ins

list_classes

Shows schedule, capacity, and available spots visible to corporate members. List available classes

list_eligible_employees

Shows plan tier, activation date, and usage status. List eligible corporate employees

list_locations

List partner locations

validate_check_in

Confirms plan eligibility and records the visit. Called when a member scans their QR code at the front desk. Validate a gym check-in

Example Prompts for Wellhub in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Wellhub immediately.

"How many Wellhub check-ins did we have this week?"

"Verify if Alex Johnson is eligible for the Silver tier."

"List the upcoming Yoga classes available to Wellhub members at our main location."

Troubleshooting Wellhub MCP Server with LlamaIndex

Common issues when connecting Wellhub to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Wellhub + LlamaIndex FAQ

Common questions about integrating Wellhub MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Wellhub tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.