Paddle 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 Paddle 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 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 Paddle. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Paddle?"
)
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 Paddle MCP Server
Bring the Paddle Billing API directly into your AI workflows. Acting as your Merchant of Record (MoR) interface, this integration allows your agent to seamlessly query customer billing states, manage SaaS subscriptions, retrieve invoice ledgers, and pause actively churning plans natively.
LlamaIndex agents combine Paddle tool responses with indexed documents for comprehensive, grounded answers. Connect 10 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
- Customers & Billing Details — List and search all CRM accounts managed by Paddle and extract their exact tax identification boundaries
- Subscription Lifecycle — Inspect active or past-due subscriptions, cancel recurring flows dynamically, or pause an active schedule right from chat
- Transactions & Ledgering — Fetch bulk atomic transactions matching exact one-off payments, prorations, and historical subscription renewals
- Catalog Explorer — List your products and retrieve localized checkout prices and native tax-inclusive pricing definitions
The Paddle 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 Paddle to LlamaIndex via MCP
Follow these steps to integrate the Paddle 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 Paddle
Why Use LlamaIndex with the Paddle MCP Server
LlamaIndex provides unique advantages when paired with Paddle through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Paddle tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Paddle tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Paddle, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Paddle tools were called, what data was returned, and how it influenced the final answer
Paddle + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Paddle MCP Server delivers measurable value.
Hybrid search: combine Paddle real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Paddle 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 Paddle for fresh data
Analytical workflows: chain Paddle queries with LlamaIndex's data connectors to build multi-source analytical reports
Paddle MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Paddle to LlamaIndex via MCP:
cancel_subscription
Can be set to effective immediately or at the end of the current billing period. Cancel an active subscription
get_customer_details
Get details for a specific customer
get_subscription_details
Get details for a specific subscription
get_transaction_details
Get details for a specific transaction
list_catalog_prices
List all pricing definitions
list_catalog_products
List all products
list_customers
List all customers in Paddle
list_subscriptions
List all subscriptions
list_transactions
List all billing transactions
pause_subscription
Pause an active subscription
Example Prompts for Paddle in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Paddle immediately.
"Find the subscription details for sub_01h9z2..."
"List our most recent revenue transactions on Paddle."
"Cancel subscription sub_active123 at the end of the billing cycle."
Troubleshooting Paddle MCP Server with LlamaIndex
Common issues when connecting Paddle to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPaddle + LlamaIndex FAQ
Common questions about integrating Paddle 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 Paddle 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 Paddle to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.