How to Use the Chargify MCP in LlamaIndex

Index your Chargify billing history into LlamaIndex to query customer MRR and plan data using natural language.

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Connect Chargify MCP to LlamaIndex

Create your Vinkius account to connect Chargify 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 Chargify with LlamaIndex

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Index Chargify data for smarter LlamaIndex RAG

Turn your billing records into a searchable knowledge base. By running `list_subscriptions` and indexing the output, you allow your agent to answer questions about customer churn using historical data. Ground your agent's responses in factual billing records. Instead of guessing, the system pulls exact MRR figures from your account to provide accurate answers.

Query your Chargify catalog via LlamaIndex

Search through your product handles and plan details instantly. Use `list_catalog_products` to pull the latest catalog data into your index for fast retrieval. Ask your agent to compare plans or check availability. The system parses the catalog data you indexed and gives you precise information without hallucination.

Ground AI decisions on Chargify customer data

Verify customer identities before taking actions like `cancel_subscription`. By indexing `get_customer_details`, your agent knows exactly who it is modifying. Connect the agent to your verified data store. It cross-references the customer email from your index before executing any billing change.

Setup guide

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

Use the tool spec to fetch billing data and ingest it into your vector store. This makes your subscription records available for semantic search queries.

Once indexed, your agent performs semantic searches across your entire billing history. You get answers grounded in the specific data points retrieved from the API.

The data is mapped directly from your account to the index. You control which tools the agent uses, ensuring the context remains accurate and relevant.

All records are isolated within your local indexing pipeline. Sensitive data like customer names and email strings are never stored in public caches.

Refresh your tool calls to pull the latest subscription states. Your agent then updates the index so your answers always reflect the current billing reality.

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