How to Use the Recharge MCP in LlamaIndex

Q: How do I index Recharge product catalogs in LlamaIndex?

You run listproducts through the MCP client and pass the output to LlamaIndex Document objects. From there, you can build a VectorStoreIndex that your agent queries whenever customers ask about subscription options.

Q: Can LlamaIndex update a Recharge subscription?

Yes, by using the updatesubscription tool within an agentic loop. LlamaIndex agents use function-calling to execute this tool directly when a user requests a change to their delivery frequency or product choices.

Q: How do I prevent LlamaIndex from hallucinating Recharge data?

You force the agent to use getsubscriptiondetails before answering any account questions. Grounding the response in the live payload returned by this MCP Server ensures the agent only states actual subscription facts.

Q: Can I query shipping addresses with this setup?

Yes, the listshippingaddresses tool retrieves customer locations. Your agent can read these addresses to verify regional shipping restrictions before recommending new products from your catalog.

Index live Recharge customer and subscription data directly into your LlamaIndex vector store for RAG queries.

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Connect Recharge MCP to LlamaIndex

Create your Vinkius account to connect Recharge 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 Recharge with LlamaIndex

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Index products and subscriptions in LlamaIndex

The `list_products` tool retrieves your current inventory catalog, and `list_subscriptions` fetches active customer plans. LlamaIndex indexes these outputs directly into your vector database, turning raw commerce data into searchable document nodes. Your agent queries this index to answer customer questions about plan terms or product specs. It matches the user's query against actual Recharge data instead of guessing.

Search transactional records using the MCP Server

The `list_subscription_orders` tool retrieves completed transaction logs, which your LlamaIndex pipeline can combine with unstructured support files. This MCP Server integration allows you to run semantic search across both live API records and PDF manuals. When a customer asks about a specific order status, the agent pulls the record, updates the index, and generates a response grounded in the exact transaction history.

Map customer billing profiles for RAG

The `get_customer` tool extracts profile details, and `list_billing_charges` pulls historical invoices. LlamaIndex ingestion pipelines can structure this data into node graphs, making it easy to query payment trends. This setup lets you build context-rich support engines. The agent reads the parsed nodes to understand a customer's lifetime value before suggesting subscription updates.

Setup guide

Set up Recharge 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 Recharge 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 Recharge tools.",
)
response = await agent.run("List recent Recharge 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 Recharge. 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 Recharge MCP in LlamaIndex

You run `list_products` through the MCP client and pass the output to LlamaIndex Document objects. From there, you can build a VectorStoreIndex that your agent queries whenever customers ask about subscription options.

Yes, by using the `update_subscription` tool within an agentic loop. LlamaIndex agents use function-calling to execute this tool directly when a user requests a change to their delivery frequency or product choices.

You force the agent to use `get_subscription_details` before answering any account questions. Grounding the response in the live payload returned by this MCP Server ensures the agent only states actual subscription facts.

Yes, the `list_shipping_addresses` tool retrieves customer locations. Your agent can read these addresses to verify regional shipping restrictions before recommending new products from your catalog.

Your customer profiles and shipping addresses are never sent to external indexing servers. The Vinkius MCP Server handles the API authorization locally, passing only the final structured text to your LLM and vector store.

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