How to Use the Layup MCP in LlamaIndex

Q: Does Layup allow filtering tools in LlamaIndex?

You can use an allowedtools filter to limit which functions your agent can access. This keeps the execution scope tight and focused on specific data retrieval tasks.

Q: How do I access resource data from Layup in LlamaIndex?

Set includeresources to true during your tool spec initialization. This gives your agent the ability to read the underlying data structures directly from the server.

Index your Layup order history in LlamaIndex to create a searchable knowledge base grounded in live financial data.

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Connect Layup MCP to LlamaIndex

Create your Vinkius account to connect Layup 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 Layup with LlamaIndex

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Ground LlamaIndex queries in Layup data

Use `list_orders` to pull active lay-by plans directly into your vector store. Your agent then queries this indexed data to provide answers based on real-time order status. This prevents your agent from hallucinating details about customer payments. It pulls the ground truth from your account every time a query is executed.

Search payment history with LlamaIndex

Index the results of `get_payment` and `list_payments` to allow for semantic search across transaction logs. You can ask your agent about specific deposit patterns or historical trends. This makes your historical data queryable alongside your documents. It turns raw API output into a searchable asset for your support team.

Manage customer profiles in LlamaIndex

Retrieve shopper data via `get_customer` and store it in your knowledge base. Your agent references these profiles to answer specific questions about account standing. This integration ensures your RAG application has access to the latest checkout information. It updates the index whenever you refresh the tool output.

Setup guide

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

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Common questions about Layup MCP in LlamaIndex

Use the MCP tool spec to convert your server tools into a list compatible with the function agent. LlamaIndex then handles the indexing of the results into your vector store.

You can use an allowed_tools filter to limit which functions your agent can access. This keeps the execution scope tight and focused on specific data retrieval tasks.

Set include_resources to true during your tool spec initialization. This gives your agent the ability to read the underlying data structures directly from the server.

Your agent will wait for the tool output before proceeding with the query. Ensure your network connection to the server is stable to avoid latency spikes during indexing.

Yes, your customer data is processed in a secure, isolated sandbox. We ensure that only authorized tokens can access the information during your RAG indexing process.

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