Tango MCP Server for LlamaIndexGive LlamaIndex instant access to 12 tools to Create Account, Create Customer, Create Order, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Tango 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 Tango app connector for LlamaIndex is a standout in the Money Moves category — giving your AI agent 12 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 Tango. "
"You have 12 tools available."
),
)
response = await agent.run(
"What tools are available in Tango?"
)
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 Tango MCP Server
Connect your Tango (formerly Tango Card) reward platform account to any AI agent and simplify how you distribute digital gift cards, manage customers, and monitor funding accounts through natural conversation.
LlamaIndex agents combine Tango tool responses with indexed documents for comprehensive, grounded answers. Connect 12 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
- Catalog Discovery — Browse the full global catalog of brands, including gift cards, prepaid cards, and non-profit donations.
- Reward Distribution — Place and automate orders for digital rewards delivered via email instantly.
- Customer & Account Management — List, create, and manage customer groups and their associated funding accounts.
- Financial Oversight — Check real-time account balances, list funding sources, and retrieve current exchange rates.
- Order Tracking — Monitor your reward history and fetch detailed status and credentials for specific order IDs.
- Scalable Rewards — Coordinate bulk payouts and loyalty incentives directly from Claude, Cursor, or any MCP client.
The Tango MCP Server exposes 12 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 12 Tango tools available for LlamaIndex
When LlamaIndex connects to Tango through Vinkius, your AI agent gets direct access to every tool listed below — spanning gift-cards, rewards-api, incentives, 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.
Create a new funding account
Create a new customer
Place a reward order
Get account balance
List available reward brands
Get customer details
Get currency exchange rates
Get order status
List accounts for a customer
List all customers
List funding sources
List recent orders
Connect Tango to LlamaIndex via MCP
Follow these steps to wire Tango 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 Tango MCP Server
LlamaIndex provides unique advantages when paired with Tango through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Tango tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Tango tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Tango, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Tango tools were called, what data was returned, and how it influenced the final answer
Tango + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Tango MCP Server delivers measurable value.
Hybrid search: combine Tango real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Tango 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 Tango for fresh data
Analytical workflows: chain Tango queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Tango in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Tango immediately.
"Show me all available gift card brands in the catalog."
"What is the current balance of account 'acc_10293'?"
"Send a $25 Amazon gift card (UTID: AMZN-US-2500) to 'john.doe@example.com'."
Troubleshooting Tango MCP Server with LlamaIndex
Common issues when connecting Tango to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTango + LlamaIndex FAQ
Common questions about integrating Tango MCP Server with LlamaIndex.