How to Use the Assembled MCP in LlamaIndex

Q: How do I query Assembled data through LlamaIndex?

Set up a BasicMCPClient with your Vinkius URL. Convert it using McpToolSpec and pass the async tool list to your agent. Your RAG setup can now search live schedules.

Q: Does the Assembled MCP Server support LlamaIndex async calls?

It handles concurrent fetches natively. You call totoollistasync() to grab tools without blocking your event loop.

Index Assembled workforce schedules directly into your LlamaIndex RAG applications.

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Connect Assembled MCP to LlamaIndex

Create your Vinkius account to connect Assembled 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 Assembled with LlamaIndex

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Ground RAG in Assembled MCP Server Data

Static documents cannot answer questions about today's staffing. `McpToolSpec` pulls live shift data through `list_schedules` and drops it straight into your vector store. The query engine now knows exactly who is working the morning shift. Adding `list_forecasts` gives your index context on expected ticket volumes. When a user asks why hold times are high, the system checks the math instead of hallucinating an excuse. You get answers backed by hard API metrics.

Index Real-Time Queue States

Support operations move faster than daily batch jobs. A FunctionAgent executes `list_agent_states` to read exactly what your team is doing right now. The output becomes searchable context for immediate operational queries. Combining this with `list_queues` creates a complete picture of your floor via this MCP connection. The framework sees forty tickets in the billing queue and only two agents active. Your RAG app flags the bottleneck immediately using live data.

Vectorize Your Organizational Structure

Querying support capacity requires understanding how the department is built. Fetching `list_teams` maps out the hierarchy for semantic search. The index learns which groups handle specific product lines. Populating the rest of the directory happens through `list_users`. LlamaIndex chunks these profiles so you can ask natural language questions about specific staff members. It turns a flat employee list into a queryable knowledge graph.

Setup guide

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

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Common questions about Assembled MCP in LlamaIndex

Set up a `BasicMCPClient` with your Vinkius URL. Convert it using `McpToolSpec` and pass the async tool list to your agent. Your RAG setup can now search live schedules.

No, this server only exposes read operations. Your RAG system reads the current status, but cannot force a user offline.

It handles concurrent fetches natively. You call `to_tool_list_async()` to grab tools without blocking your event loop.

Forecasts change daily, so querying them on demand makes more sense than static indexing. Use the tools directly in your query engine rather than storing stale predictions.

The zero-trust architecture ensures data stays between your client and the endpoint. Vinkius drops the connection state instantly after fetching the directory. This MCP token never leaks into the vector store embeddings.

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