Amilia 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 Amilia 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 Amilia. "
"You have 9 tools available."
),
)
response = await agent.run(
"What tools are available in Amilia?"
)
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 Amilia MCP Server
Connect your Amilia (SmartRec) account to your AI agent to unlock professional recreation management and participant orchestration. From auditing activity programs and monitoring attendance to managing household accounts and tracking registrations, your agent handles your community operations through natural conversation.
LlamaIndex agents combine Amilia 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
- Program & Activity Orchestration — List and manage recreational programs, activities, and specific class occurrences
- Account & Contact Oversight — Retrieve detailed profiles for families/households and their individual contacts
- Registration Tracking — Audit sign-ups and retrieve registration histories for specific accounts
- Attendance Management — Retrieve rosters and check-in statuses for specific event occurrences
- Operational Insights — Quickly identify popular activities or retrieve attendance reports directly from your chat interface
The Amilia 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 Amilia to LlamaIndex via MCP
Follow these steps to integrate the Amilia 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 Amilia
Why Use LlamaIndex with the Amilia MCP Server
LlamaIndex provides unique advantages when paired with Amilia through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Amilia tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Amilia tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Amilia, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Amilia tools were called, what data was returned, and how it influenced the final answer
Amilia + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Amilia MCP Server delivers measurable value.
Hybrid search: combine Amilia real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Amilia 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 Amilia for fresh data
Analytical workflows: chain Amilia queries with LlamaIndex's data connectors to build multi-source analytical reports
Amilia MCP Tools for LlamaIndex (9)
These 9 tools become available when you connect Amilia to LlamaIndex via MCP:
get_account_details
Get account profile
get_attendance
Get attendance roster
get_program_details
Get program metadata
list_accounts
List family accounts
list_activities
List program activities
list_activity_occurrences
List activity schedules
list_contacts
List account contacts
list_programs
g. Summer Camp, Fall Sessions). List recreational programs
list_registrations
List account registrations
Example Prompts for Amilia in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Amilia immediately.
"List all active programs in my organization."
"Show me the contacts associated with account ID 'acc_12345'."
"Get the attendance roster for occurrence ID 'occ_98765'."
Troubleshooting Amilia MCP Server with LlamaIndex
Common issues when connecting Amilia to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAmilia + LlamaIndex FAQ
Common questions about integrating Amilia 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 Amilia 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 Amilia to LlamaIndex
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.