Orb MCP Server for LlamaIndexGive LlamaIndex instant access to 10 tools to Cancel Subscription, Create Customer, Create Ledger Entry, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Orb 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 for LlamaIndex
The Orb MCP Server for LlamaIndex is a standout in the Data Management category — giving your AI agent 10 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 Orb. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Orb?"
)
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 Orb MCP Server
Connect your Orb account to any AI agent to streamline your revenue operations and usage-based billing workflows through natural language.
LlamaIndex agents combine Orb 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
- Usage Ingestion — Send batches of usage events with idempotency keys to track consumption in real-time.
- Subscription Lifecycle — Create, update, and cancel subscriptions, tying customers to specific billing plans seamlessly.
- Customer Management — Provision new customers and list existing ones with full metadata and external ID mapping.
- Invoicing & Revenue — List historical invoices or fetch upcoming draft invoices to predict end-of-month billing.
- Credit Ledgers — Manage prepaid credits by creating ledger entries for increments, decrements, or expirations.
The Orb MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 10 Orb tools available for LlamaIndex
When LlamaIndex connects to Orb through Vinkius, your AI agent gets direct access to every tool listed below — spanning usage-based-billing, revenue-operations, subscription-management, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.
Cancel subscription on Orb
Cancel a subscription
Create customer on Orb
Requires name and email. Create a new customer in Orb
Create ledger entry on Orb
Create a ledger entry for credits
Create subscription on Orb
Create a subscription for a customer
Fetch ledger on Orb
Fetch credit ledger for a customer
Get upcoming invoice on Orb
Fetch upcoming invoice for a subscription
Ingest events on Orb
Events require customer_id, event_name, timestamp, idempotency_key, and properties. Ingest usage events into Orb
List customers on Orb
List customers in Orb
List invoices on Orb
List invoices
Update subscription on Orb
Update an existing subscription
Connect Orb to LlamaIndex via MCP
Follow these steps to wire Orb into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind 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 Orb MCP Server
LlamaIndex provides unique advantages when paired with Orb through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Orb tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Orb tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Orb, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Orb tools were called, what data was returned, and how it influenced the final answer
Orb + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Orb MCP Server delivers measurable value.
Hybrid search: combine Orb real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Orb 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 Orb for fresh data
Analytical workflows: chain Orb queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Orb in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Orb immediately.
"List the last 5 customers created in Orb."
"Ingest a usage event for customer cust_123: 50 units of 'api_requests'."
"What is the upcoming invoice amount for subscription sub_987?"
Troubleshooting Orb MCP Server with LlamaIndex
Common issues when connecting Orb to LlamaIndex through Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpOrb + LlamaIndex FAQ
Common questions about integrating Orb 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?
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