Pike13 MCP Server for LlamaIndex 9 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Pike13 as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
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 Pike13. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Pike13?"
)
print(response)
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 Pike13 MCP Server
Connect your Pike13 studio to any AI agent and manage your fitness business through natural conversation.
LlamaIndex agents combine Pike13 tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through 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
- Events — View scheduled classes and sessions with instructors, capacity, and enrollment
- Clients — Search members by name, email, or phone with detailed profiles
- Staff — List instructors with roles, certifications, and class assignments
- Plans — Browse membership plans, class packs, and drop-in pricing
- Invoices — Track revenue, payments, refunds, and financial reporting
- Visits — Analyze check-in records for retention and engagement analytics
- Business — Access account profile and configuration
Why Pike13?
Pike13 uniquely offers a Reporting API with deep analytics — making it the best choice for data-driven studio owners who want AI-powered business intelligence. Combined with the Core API and Webhooks, it provides the most comprehensive data access in the fitness industry.
The Pike13 MCP Server exposes 9 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 Pike13 to LlamaIndex via MCP
Follow these steps to integrate the Pike13 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 9 tools from Pike13
Why Use LlamaIndex with the Pike13 MCP Server
LlamaIndex provides unique advantages when paired with Pike13 through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Pike13 tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Pike13 tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Pike13, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Pike13 tools were called, what data was returned, and how it influenced the final answer
Pike13 + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Pike13 MCP Server delivers measurable value.
Hybrid search: combine Pike13 real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Pike13 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 Pike13 for fresh data
Analytical workflows: chain Pike13 queries with LlamaIndex's data connectors to build multi-source analytical reports
Pike13 MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect Pike13 to LlamaIndex via MCP:
get_business_info
Get business account info
get_event
Get event details
get_person
Get person profile
list_events
Filter by date range. Follows JSON:API 1.0 spec. List scheduled classes/events
list_invoices
Filter by date for financial reporting. List invoices and revenue
list_plans
Includes pricing and visit limits. List service plans
list_staff
List staff members
list_visits
Key data for retention analytics. List member visits
search_people
Returns profiles, active plans, visit count, and account balance. Search clients/members
Example Prompts for Pike13 in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Pike13 immediately.
"What's our revenue this month?"
"List the staff members teaching yoga classes tomorrow."
"How many new clients bought a membership this week?"
Troubleshooting Pike13 MCP Server with LlamaIndex
Common issues when connecting Pike13 to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPike13 + LlamaIndex FAQ
Common questions about integrating Pike13 MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Pike13 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 Pike13 to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.