How to Use the Vonage MCP in LlamaIndex

Q: Can I query past WhatsApp activity with Vonage and LlamaIndex?

Yes. By indexing the results of sendwhatsappmessage, you can build a knowledge base that answers questions about previous message sends, who was contacted, and when.

Q: When using Vonage with LlamaIndex, how do I check billing?

You run the getaccountbalance tool. The result is indexed immediately, allowing you to query your historical financial data against it later on.

Ground your knowledge base with LlamaIndex and Vonage API data.

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Connect Vonage MCP to LlamaIndex

Create your Vinkius account to connect Vonage to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Vonage with LlamaIndex

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Query Account Financials via MCP Server

LlamaIndex can index critical operational data for later retrieval. You run `get_account_balance` to get the current Vonage credit balance, and that output is stored in your vector store. Later, you query your knowledge base: 'What was our account balance last week?' The answer comes grounded in real API calls, not just general text.

Index Communication Statuses

Need to know what numbers are active? Running `list_rented_numbers` pulls a list of all virtual phone lines. This output becomes indexed knowledge. This means your RAG application can answer questions like, 'Which countries do we have rented numbers in?' by querying the actual API data.

Track Communication Methods

The MCP Server allows you to index multiple communication channels. You can call `get_country_pricing` and then document the results, creating a searchable knowledge base of international rates. This structured data lets your application answer complex questions about cross-border messaging costs.

Setup guide

Set up Vonage MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Vonage MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Vonage tools.",
)
response = await agent.run("List recent Vonage data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Vonage. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Vonage MCP in LlamaIndex

The MCP Server allows you to index the results of all calls—SMS sends, Viber messages, WhatsApp messages. You create a single knowledge base that covers your entire communication history.

It provides structured API data like account balances, country pricing tables, and lists of virtual phone numbers. This is all ideal for semantic search.

Yes. By indexing the results of `send_whatsapp_message`, you can build a knowledge base that answers questions about previous message sends, who was contacted, and when.

You run the `get_account_balance` tool. The result is indexed immediately, allowing you to query your historical financial data against it later on.

The server primarily handles communication metadata: sender names, target phone numbers (E.164 format), and country codes.

Use it with your favorite AI tools

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