How to Use the Homebase MCP in LlamaIndex

Q: Can LlamaIndex query Homebase locations dynamically?

Yes, the framework calls listlocations to fetch active sites. It then uses those IDs to retrieve specific departmental lists on the fly.

Q: How does LlamaIndex handle tool filtering for Homebase?

You can use the allowedtools filter to restrict MCP tools. This ensures your LlamaIndex agent only calls safe endpoints like listlaborbudgets and stays away from sensitive staff files.

Q: Can I build a RAG app using this MCP Server?

Yes, you can feed timecard data from listtimecards directly into a vector index. This lets users search past hours and shifts using plain English.

Index Homebase schedules and timesheets into searchable LlamaIndex vector stores.

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Connect Homebase MCP to LlamaIndex

Create your Vinkius account to connect Homebase 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 Homebase with LlamaIndex

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Index live Homebase timesheets into LlamaIndex

This MCP Server lets LlamaIndex pull raw work records using `list_timecards` and index them straight into your vector database. You stop querying APIs manually. Your LlamaIndex agent queries the resulting index to find scheduling patterns. It extracts semantic trends from past shifts without constantly hitting the live server.

Ground LlamaIndex queries in real-time shift data

LlamaIndex uses `get_active_clock_ins` to verify who is on-site before answering scheduling questions. This keeps your RAG applications updated with current staff availability. The LlamaIndex agent verifies local context first. It calls `list_locations` to find the correct venue, then cross-references `list_scheduled_shifts` to verify if the roster matches reality.

Map labor structures directly to LlamaIndex nodes

LlamaIndex reads your company hierarchy using `list_departments` to build a clean knowledge graph. This structures your organizational data for semantic search. Finding specific worker details becomes instant. The framework indexes output from `list_employees` and `get_employee_profile` to answer natural language questions about team assignments.

Setup guide

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

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Common questions about Homebase MCP in LlamaIndex

Load the tools using llama-index-tools-mcp. Once loaded, you can parse the output of list_scheduled_shifts and write it directly into your document store for vector indexing.

Yes, the framework calls list_locations to fetch active sites. It then uses those IDs to retrieve specific departmental lists on the fly.

You can use the allowed_tools filter to restrict MCP tools. This ensures your LlamaIndex agent only calls safe endpoints like list_labor_budgets and stays away from sensitive staff files.

Yes, you can feed timecard data from list_timecards directly into a vector index. This lets users search past hours and shifts using plain English.

Vinkius executes the MCP Server in a secure sandbox. Only the specific shift and location data you request is pulled, and your credentials are never exposed to the LLM.

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