How to Use the LiftedWork MCP in LlamaIndex

Index your agency employment data into LlamaIndex to build RAG apps that ground your answers in actual project results.

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Connect LiftedWork MCP to LlamaIndex

Create your Vinkius account to connect LiftedWork 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 LiftedWork with LlamaIndex

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Ground agency data with LlamaIndex

LlamaIndex transforms the output of your MCP tools into a searchable knowledge base. When you call `list_tasks`, the results are indexed for semantic retrieval. This stops your agent from guessing about project statuses. Your answers are based on the actual JSON data pulled from your agency dashboard.

Query historical time entries

You can now perform semantic searches across your `list_time_entries` history. The index captures the context of every entry for better retrieval accuracy. This helps when you need to answer questions about past project hours. The agent finds relevant data points even if the terminology varies slightly.

Build unified search indexes

Combine your live agency API data with local documents using standard tool specs. You fetch project details via `list_projects` and merge them into your existing vector store. This creates a single source of truth for your agent. You query the index to get precise information about clients and their active projects.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by LiftedWork. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about LiftedWork MCP in LlamaIndex

You use the tool spec to convert your MCP tools into a format LlamaIndex understands. The agent then indexes the results for your RAG pipeline.

By grounding your agent in retrieved API data, you remove the need for guessing. The agent answers based on the index built from your actual `list_tasks` output.

It takes a few lines of code to initialize the client and convert the tools. Once done, you can start indexing your agency records immediately.

You control the refresh frequency based on your needs. For real-time updates, trigger a tool call immediately before your query.

Your agency data is handled through an ephemeral sandbox. No sensitive information persists outside your session once the index is cleared.

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