Recharge MCP Server for LlamaIndexGive LlamaIndex instant access to 11 tools to Cancel Subscription, Get Customer, Get Order, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Recharge as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Recharge app connector for LlamaIndex is a standout in the Money Moves category — giving your AI agent 11 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Recharge. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Recharge?"
)
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 Recharge MCP Server
Connect your Recharge account to any AI agent and simplify your subscription management and recurring billing workflows through natural conversation.
LlamaIndex agents combine Recharge tool responses with indexed documents for comprehensive, grounded answers. Connect 11 tools through 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
- Subscription Management — List all active and cancelled subscriptions, retrieve detailed metadata, and update parameters programmatically
- Customer Database — Query your database of subscribers and retrieve detailed profile and billing info
- Order Tracking — Monitor processed subscription orders and stay on top of your fulfillment pipeline
- Financial Insights — Access processed charges and billing history to understand your recurring revenue
- Direct Control — Modify subscription quantities and scheduled charge dates without manual dashboard navigation
The Recharge MCP Server exposes 11 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.
All 11 Recharge tools available for LlamaIndex
When LlamaIndex connects to Recharge through Vinkius, your AI agent gets direct access to every tool listed below — spanning subscriptions, recurring-billing, shopify-subscriptions, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Cancel a subscription
Get details for a specific customer
Get details for a specific order
Get details for a specific subscription
List billing charges
List Recharge customers
List all subscription products
List customer addresses
List processed orders
List Recharge subscriptions
Update an existing subscription
Connect Recharge to LlamaIndex via MCP
Follow these steps to wire Recharge into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Recharge MCP Server
LlamaIndex provides unique advantages when paired with Recharge through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Recharge tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Recharge tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Recharge, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Recharge tools were called, what data was returned, and how it influenced the final answer
Recharge + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Recharge MCP Server delivers measurable value.
Hybrid search: combine Recharge real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Recharge 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 Recharge for fresh data
Analytical workflows: chain Recharge queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Recharge in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Recharge immediately.
"List all active subscriptions in Recharge."
"Show me all active subscriptions that are due for renewal in the next 7 days."
"Show me the churn analysis for the last 30 days with cancellation reasons."
Troubleshooting Recharge MCP Server with LlamaIndex
Common issues when connecting Recharge to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpRecharge + LlamaIndex FAQ
Common questions about integrating Recharge MCP Server with LlamaIndex.