How do I get started?

Subscribe, enter your API credentials (your generated Hubstaff PAT via **User Settings → Personal access tokens**), and you're set. No code, no environment files, no postbacks — just connect and audit team activity with natural text.

Can my AI check a single associate's daily activities quickly?

Yes! Direct your prompt to fetch all logged daily activities (or activities specifically). The agent will query Hubstaff, breaking down the tracking records and formatting them directly so you won't need to manually click through web portals.

How easy is it to gather organization and project specifics?

It essentially takes seconds explicitly asking 'List my organizations and projects.' The `list_projects` functionality traverses your environment returning the IDs you need to inspect underlying items.

Is the agent suited to handle multiple large organizational hubs at once?

Yes! Due to targeted parameter queries (e.g., retrieving timesheets by target organization), HR firms and agencies scaling hundreds of contractors can extract clean textual aggregations pain-free via simple prompts.

Hubstaff MCP Server for LlamaIndex 9 tools — connect in under 2 minutes

Name: Hubstaff
Availability: InStock
Author: Vinkius

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 9 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Hubstaff as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Hubstaff. "
            "You have 9 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Hubstaff?"
    )
    print(response)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Hubstaff MCP Server

Connect your Hubstaff tracking account to any AI agent and bring your entire workforce analytics straight to a conversational interface.

LlamaIndex agents combine Hubstaff tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

What you can do

Track Activities — Investigate how time is allocated pulling detailed tracked activities and daily activity snapshots
Workforce Management — Analyze organizations, users, and tasks without toggling native dashboard panels
Project Analytics — Determine the list of created projects and fetch precise timesheets for agile billing summaries

The Hubstaff MCP Server exposes 9 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Hubstaff to LlamaIndex via MCP

Follow these steps to integrate the Hubstaff MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 9 tools from Hubstaff

Why Use LlamaIndex with the Hubstaff MCP Server

LlamaIndex provides unique advantages when paired with Hubstaff through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine Hubstaff tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain Hubstaff tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query Hubstaff, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what Hubstaff tools were called, what data was returned, and how it influenced the final answer

Hubstaff + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the Hubstaff MCP Server delivers measurable value.

Hybrid search: combine Hubstaff real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query Hubstaff to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Hubstaff for fresh data

Analytical workflows: chain Hubstaff queries with LlamaIndex's data connectors to build multi-source analytical reports

Hubstaff MCP Tools for LlamaIndex (9)

These 9 tools become available when you connect Hubstaff to LlamaIndex via MCP:

get_organization

Get parameters surrounding an organization

get_project

Retrieve single project structure

get_user

Fetch targeted user details

list_activities

Retrieve global organizational activities logged

list_organizations

Retrieve the parent organizations

list_projects

Retrieve all active projects linked to an organization

list_tasks

Retrieve operational sub-tasks per project

list_time_entries

Read explicitly billed or logged temporal time blocks

list_users

Retrieve staff and employees under the hub

Example Prompts for Hubstaff in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Hubstaff immediately.

"Can you check my Hubstaff dashboard and list the organizations I have access to?"

"Retrieve all the timesheets available so I can verify billing."

"List today's daily activities tracked in the organization."

Troubleshooting Hubstaff MCP Server with LlamaIndex

Common issues when connecting Hubstaff to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Hubstaff + LlamaIndex FAQ

Common questions about integrating Hubstaff MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Hubstaff tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.