Chargebee MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Chargebee as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Chargebee. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Chargebee?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Chargebee MCP Server
Connect your Chargebee environment to any AI agent and take absolute control of your SaaS revenue operations by simply chatting. Bypass massive spreadsheets and complex financial dashboards.
LlamaIndex agents combine Chargebee tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Customers — List existing accounts, retrieve specific financial details (outstanding balances), or create brand new B2B accounts instantly
- Subscriptions — Inspect active, trailing, or cancelled plans. Pause renewals, trace MRR, or irreversibly cancel subscriptions mid-term
- Invoices — Retrieve active billing logs and check if a payment gateway approved or declined a specific charge
- Checkout & Catalog — Enumerate product lines and generate ephemeral, secure Hosted Checkout URLs to capture customer cards on the fly
The Chargebee MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Chargebee to LlamaIndex via MCP
Follow these steps to integrate the Chargebee MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Chargebee
Why Use LlamaIndex with the Chargebee MCP Server
LlamaIndex provides unique advantages when paired with Chargebee through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Chargebee tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Chargebee tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Chargebee, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Chargebee tools were called, what data was returned, and how it influenced the final answer
Chargebee + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Chargebee MCP Server delivers measurable value.
Hybrid search: combine Chargebee real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Chargebee to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Chargebee for fresh data
Analytical workflows: chain Chargebee queries with LlamaIndex's data connectors to build multi-source analytical reports
Chargebee MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Chargebee to LlamaIndex via MCP:
cancel_subscription
Irreversibly vaporize explicit validations extracting rich Churn flags
create_customer
Provision a highly-available JSON Payload generating hard Customer records
generate_hosted_checkout
Dispatch an automated validation check routing explicit Payment UI
get_customer_details
Perform structural extraction of properties driving active Account logic
get_subscription_details
Inspect deep internal arrays mitigating specific Plan Math
list_catalog_items
Retrieve the exact structural matching verifying Product mapping
list_customers
Identify bounded CRM records inside the Headless Chargebee Platform
list_invoices
Enumerate explicitly attached structured rules exporting active Billing
list_subscriptions
Retrieve explicit Cloud logging tracing explicit Recurring limits
pause_subscription
Identify precise active arrays spanning native Pause tracking
Example Prompts for Chargebee in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Chargebee immediately.
"Create a new customer profile for John Doe at john@acme.com."
"Cancel subscription sub_4001, but wait until the end of the term."
"Review my invoices and point out any recent declines."
Troubleshooting Chargebee MCP Server with LlamaIndex
Common issues when connecting Chargebee to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpChargebee + LlamaIndex FAQ
Common questions about integrating Chargebee MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect Chargebee with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Chargebee to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.