How to Use the Hullo MCP in LlamaIndex

Q: Can LlamaIndex search through Hullo member profiles?

Yes. The framework indexes the output of listmembers so you can run semantic queries against your entire coworking directory.

Q: Does the server support data access filters?

You control exactly what the agent sees. Set includeresources=True to let the index read specific workspace documents alongside the tool outputs.

Q: How do I trigger Hullo messages from LlamaIndex?

Give your FunctionAgent access to sendmessage. It formulates the JSON payload based on its indexed knowledge and dispatches the text.

Index your coworking community data and chat history using the Hullo MCP Server with LlamaIndex.

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Connect Hullo MCP to LlamaIndex

Create your Vinkius account to connect Hullo 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 Hullo with LlamaIndex

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Claude

Perplexity

Query Your Workspace Roster

`list_members` and `get_member` pull your tenant directory straight into your vector store. Your LlamaIndex application fetches the raw API data and embeds it for semantic search. You stop guessing who occupies which desk. When a user asks about a specific tenant, the engine retrieves the exact profile details instead of hallucinating an answer.

Index Conversations

`list_conversations` extracts the community dialogue from your workspace. The agent pulls these threads through the MCP standard and turns them into a searchable knowledge base. Ask your system why people keep complaining about the Wi-Fi. The index cross-references `get_conversation` outputs to give you answers grounded in actual member complaints.

LlamaIndex MCP Server Setup

`create_member` handles the administrative data entry while `send_message` handles the introduction. Your FunctionAgent executes these tools based on the allowed tools filter you define. Integrating this requires passing your client to McpToolSpec. You get a unified index that reads from your documents and writes directly to your coworking platform.

Setup guide

Set up Hullo 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 Hullo 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 Hullo tools.",
)
response = await agent.run("List recent Hullo data")

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Common questions about Hullo MCP in LlamaIndex

Install llama-index-tools-mcp. Set up a BasicMCPClient and pass it to your tool spec before calling the async tool list method.

Yes. The framework indexes the output of list_members so you can run semantic queries against your entire coworking directory.

You control exactly what the agent sees. Set include_resources=True to let the index read specific workspace documents alongside the tool outputs.

Give your FunctionAgent access to send_message. It formulates the JSON payload based on its indexed knowledge and dispatches the text.

We operate a zero-trust architecture. Desk booking records and member check-in logs pass through an isolated environment. Nothing persists after your query finishes.

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