How to Use the Apex27 MCP in LlamaIndex

Q: Can LlamaIndex search through Apex27 tenant applications?

Yes, by calling listcontacts and indexing the results, LlamaIndex lets you run semantic queries over your applicant pool. You can search for specific tenant requirements without manual database filtering.

Q: Does LlamaIndex support live querying of Apex27 work orders?

Yes, you can register listworkorders as a query engine tool. This MCP connection pulls the latest status live from the CRM instead of relying on cached data.

Index your Apex27 real estate listings into LlamaIndex to build search engines for properties and tenant histories.

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Connect Apex27 MCP to LlamaIndex

Create your Vinkius account to connect Apex27 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 Apex27 with LlamaIndex

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Index property details for semantic LlamaIndex search

To retrieve deep specifications for any listing in your Apex27 database, use the `get_property_details` tool. LlamaIndex takes this raw text and indexes it directly into your vector store for instant semantic search. Instead of matching exact keywords, your agent can search your indexed real estate database using natural language queries like 'suburban houses with big yards.' The LlamaIndex pipeline pulls the relevant property IDs directly from the vector index.

Build RAG pipelines using this MCP Server

By exposing all active maintenance requests directly to your LlamaIndex retrieval pipeline, the `list_work_orders` tool keeps your agent informed. Queries to this tool ground the agent's answers in active tenant issues. This MCP Server setup avoids hallucinations by forcing the model to rely only on live CRM data when answering maintenance questions. You get factual, up-to-date responses based on actual work order statuses.

Query applicant and vendor records semantically

When the `list_contacts` tool fetches your entire database of applicants, vendors, and landlords, LlamaIndex indexes these profiles immediately. This matching process lets your agent quickly find candidates for new properties. By combining this tool with `list_appointments`, the agent can cross-reference upcoming viewings with historical applicant preferences. Such integration turns your static CRM into an active, searchable knowledge base.

Setup guide

Set up Apex27 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 Apex27 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 Apex27 tools.",
)
response = await agent.run("List recent Apex27 data")

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Common questions about Apex27 MCP in LlamaIndex

You load the tools using the LlamaIndex MCP tool spec and convert them for your agent. The agent can then call `list_properties` to pull raw text and write it directly to your vector index.

Yes, by calling `list_contacts` and indexing the results, LlamaIndex lets you run semantic queries over your applicant pool. You can search for specific tenant requirements without manual database filtering.

Yes, you can register `list_work_orders` as a query engine tool. This MCP connection pulls the latest status live from the CRM instead of relying on cached data.

Vinkius handles the authentication handshake, giving you a single secure endpoint. You pass this URL to your LlamaIndex client initialization, and the framework handles the tool schema mapping.

All applicant names and phone numbers are processed in memory within your private environment. No CRM records are stored on external servers, keeping your tenant database fully compliant with local privacy laws.

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