How to Use the Condeco (Eptura Engage) MCP in LlamaIndex

Q: How does the retrieval-augmented generation handle live Condeco changes?

Your LlamaIndex pipeline queries getroomavailability in real-time before finalizing any booking. This prevents your agent from attempting to book a desk that was reserved minutes ago by another colleague.

Index your Condeco (Eptura Engage) workspace schedules into LlamaIndex to query real-time office availability.

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Connect Condeco (Eptura Engage) MCP to LlamaIndex

Create your Vinkius account to connect Condeco (Eptura Engage) 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 Condeco (Eptura Engage) with LlamaIndex

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Indexing real-time room availability in LlamaIndex

Your LlamaIndex RAG pipeline queries live office schedules through the Condeco (Eptura Engage) MCP Server using `get_room_availability`. The results go straight into your vector store, so your agent answers workspace questions based on live data, not static calendar exports. This setup grounds your agent in reality. You won't have to worry about your agent inventing rooms or recommending spaces that are already booked for the afternoon.

Semantic search over office booking logs

The `list_bookings` tool pulls historical reservation logs directly into your LlamaIndex vector store. Your agent runs semantic queries over these indexed bookings to spot patterns in how your team uses the office. You configure this using `McpToolSpec` to feed the booking data straight into your index. This turns raw real estate logs into an active, queryable knowledge base for office managers.

Desk mapping and automated reservations

The `list_desks` tool retrieves physical hot desk capacities and layouts for your LlamaIndex agents to index. When a user requests a quiet workspace, the agent searches the index and calls `book_desk` to reserve the exact coordinates. You can also use `cancel_desk_booking` to release spaces when your index detects a user's schedule has changed. This keeps your physical office map synchronized with actual employee needs.

Setup guide

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

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Common questions about Condeco (Eptura Engage) MCP in LlamaIndex

You use the BasicMCPClient to connect to the MCP server endpoint, then wrap it in McpToolSpec. Your LlamaIndex agent calls list_bookings to retrieve raw reservation data and load it directly into your vector index.

Yes, by passing the tools from McpToolSpec to your FunctionAgent, the agent can execute book_room based on semantic queries. If a user asks for a room with a projector, the agent searches the index and books the matching space.

Yes, you can restrict your LlamaIndex agent to specific Condeco (Eptura Engage) tools like list_locations and get_room_availability while blocking write operations like cancel_room_booking.

Your LlamaIndex pipeline queries get_room_availability in real-time before finalizing any booking. This prevents your agent from attempting to book a desk that was reserved minutes ago by another colleague.

This MCP Server runs within a zero-trust V8 sandbox that handles your corporate real estate occupancy records securely. Your physical office layout data is processed in ephemeral memory and is never stored by Vinkius.

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