MoonClerk 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 MoonClerk 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 MoonClerk. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in MoonClerk?"
)
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 MoonClerk MCP Server
Connect your MoonClerk account to your AI agent and take control of your recurring revenue and customer billing through natural conversation.
LlamaIndex agents combine MoonClerk 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
- Payment Tracking — List all transactions and get real-time status updates, amounts, and currency info.
- Customer & Plan Management — Access customer profiles, recurring payment plans, and active subscriptions.
- Form Oversight — List and inspect your payment forms to stay organized.
- Deep Data Inspection — Fetch complete metadata for specific customers, payments, or plans using their unique IDs.
The MoonClerk 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 MoonClerk to LlamaIndex via MCP
Follow these steps to integrate the MoonClerk 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 MoonClerk
Why Use LlamaIndex with the MoonClerk MCP Server
LlamaIndex provides unique advantages when paired with MoonClerk through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine MoonClerk tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain MoonClerk tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query MoonClerk, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what MoonClerk tools were called, what data was returned, and how it influenced the final answer
MoonClerk + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the MoonClerk MCP Server delivers measurable value.
Hybrid search: combine MoonClerk real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query MoonClerk 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 MoonClerk for fresh data
Analytical workflows: chain MoonClerk queries with LlamaIndex's data connectors to build multi-source analytical reports
MoonClerk MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect MoonClerk to LlamaIndex via MCP:
get_customer
Get specific customer details
get_form
Get specific form details
get_payment
Get details for a specific payment
get_plan
Get specific plan details
get_subscription
Get specific subscription info
list_customers
List MoonClerk customers
list_forms
List payment forms
list_payments
List all payments
list_plans
List available payment plans
list_subscriptions
List active subscriptions
Example Prompts for MoonClerk in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with MoonClerk immediately.
"List my last 5 payments received on MoonClerk."
"What recurring payment plans do I have configured?"
"Show me the details for the payment form with ID form_123."
Troubleshooting MoonClerk MCP Server with LlamaIndex
Common issues when connecting MoonClerk to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpMoonClerk + LlamaIndex FAQ
Common questions about integrating MoonClerk 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 MoonClerk 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 MoonClerk to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.