How to Use the HelloAsso MCP in LlamaIndex

Index your HelloAsso data into LlamaIndex to build searchable, knowledge-augmented agents for your non-profit.

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Connect HelloAsso MCP to LlamaIndex

Create your Vinkius account to connect HelloAsso to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup HelloAsso with LlamaIndex

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Index HelloAsso data for semantic search

Use LlamaIndex to turn your HelloAsso data into a searchable knowledge base. By calling `list_sold_items` or `list_orders`, the agent ingests records into a vector store for persistent, grounded retrieval. This prevents the agent from hallucinating about your financial history. It queries the actual index created from your latest API pulls.

Build RAG apps with HelloAsso MCP Server

Combine live API calls with existing documents in a unified LlamaIndex structure. The agent uses `get_organization_details` to fetch context that informs how it answers questions about your association's performance. Your RAG application becomes smarter as it gathers more data. It correlates past `list_subscriptions` with current form data to provide deep insights.

Automate HelloAsso tool execution with FunctionAgent

LlamaIndex handles the heavy lifting of mapping natural language to tool arguments. You pass the tools to the FunctionAgent, and it executes `get_payment_details` when a user asks about a specific transaction. This creates a fluid interface for your administrative tasks. You get precise answers backed by real-time data from your HelloAsso account.

Setup guide

Set up HelloAsso MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all HelloAsso MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

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

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to HelloAsso tools.",
)
response = await agent.run("List recent HelloAsso data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by HelloAsso. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

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Common questions about HelloAsso MCP in LlamaIndex

Initialize the MCP client and pass the tools to your indexer. It will call the HelloAsso endpoints to retrieve data and store it in your vector database for future queries.

Your HelloAsso records are stored locally within your vector store. No raw data is shared with external parties, and access is strictly managed via your endpoint token.

Absolutely. Once indexed, you can ask questions like 'What is the total amount from recent memberships?' and the agent will query the `list_payments` tool to find the answer.

You can refresh your index by re-running the tool calls. LlamaIndex updates the knowledge base with the latest results from `list_forms` or `list_orders` to keep your agent current.

The index remains stable. You can add or remove tools from the spec, and LlamaIndex will adjust the available functions for your agent while keeping the historical data intact.

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