How to Use the Lead Time Analyzer MCP in LlamaIndex

Q: How do I make Lead Time Analyzer tools available to my LlamaIndex agent?

Instantiate the BasicMCPClient and pass it to McpToolSpec. From there, totoollistasync() gives you a list of tools ready to be passed to your FunctionAgent. It's a few lines of code to connect the agent to this MCP.

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Connect Lead Time Analyzer MCP to LlamaIndex

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Turn Lead Time Data into a Knowledge Base

Stop just running one-off analyses. With LlamaIndex, the output of every tool call becomes a permanent, searchable asset. When you use `analyze_lead_time_composition`, the results are automatically indexed into your vector store. This means you can ask questions in plain English later, like 'What was our average manufacturing lead time last quarter?' Your RAG application will pull the answer directly from the indexed results of past tool calls, giving you grounded facts instead of a guess.

Query Your Process Volatility

Running `evaluate_process_volatility` shows you where the unpredictability in your supply chain comes from. But a week later, that report is buried. With LlamaIndex, that data is indexed and correlated with other reports. You can build a query engine that connects volatility data with composition data. Ask 'Show me the most volatile stages for products with lead times over 60 days.' The system finds the relevant indexed tool outputs and synthesizes an answer.

A Factual MCP Server for LlamaIndex

A LlamaIndex agent can use these tools to answer complex questions that require fresh data. For instance, when asked 'What would happen if we improved supplier shipping by 5 days?', the agent can call `calculate_reduction_impacts` to get a live answer. This MCP provides the real-time data connection. The real power is combining live tool calls with your indexed knowledge base. The agent can compare the simulated impact with historical data to see if the projection is realistic. This MCP server gives your agent the ability to check its own work against past performance.

Setup guide

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

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Common questions about Lead Time Analyzer MCP in LlamaIndex

Instantiate the `BasicMCPClient` and pass it to `McpToolSpec`. From there, `to_tool_list_async()` gives you a list of tools ready to be passed to your FunctionAgent. It's a few lines of code to connect the agent to this MCP.

Yes, that's the core idea. LlamaIndex indexes the output of the tools. This lets you build a RAG pipeline that can query past lead time compositions or volatility reports using natural language.

You can create a unified index containing both your documents, like PDFs of contracts, and the structured output from this Lead Time Analyzer MCP. Your agent can then query across both data sources to get a complete picture.

Yes. When you create the tool specification, you can use the `allowed_tools` filter. This lets you grant an agent access to only `analyze_lead_time_composition`, for example, without giving it simulation capabilities.

The MCP only handles your lead time composition, impact, and volatility data during the API call. It's transmitted over TLS and immediately discarded after the response is sent. You are in full control of the indexed data that LlamaIndex stores in your own vector database.

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