How to Use the Termii MCP in LlamaIndex

Q: Can Termii handle WhatsApp messages in LlamaIndex?

Yes. The sendwhatsapp tool output is indexed alongside SMS data. This lets you build a unified view of all multi-channel interactions for any user or region.

Q: Can I track messaging history using Termii in LlamaIndex?

Definitely. By indexing every tool call, including sendsms or sendwhatsapp, you build a detailed record of who was contacted, when, and through which channel.

Indexing API data with LlamaIndex for deep insights into Termii's communications.

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Connect Termii MCP to LlamaIndex

Create your Vinkius account to connect Termii 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 Termii with LlamaIndex

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Querying Past Communication Logs

LlamaIndex indexes the results from tools like `send_whatsapp` and `send_sms`. You can then query your knowledge base to find out exactly when a specific user received an OTP code or what balance was checked last week. Instead of searching through raw logs, you ask LlamaIndex: 'What were the sender IDs used for US customers?' and get an answer grounded in the API data.

Context-Aware Messaging Decisions

You can build RAG applications where live API data informs the next step. For example, if a query reveals that the account balance is low (via `check_balance`), LlamaIndex guides your agent to send an SMS warning instead of trying WhatsApp. This makes communication decisions smarter—the knowledge base dictates the tool call, not just general LLM reasoning.

Verifying User State

The MCP Server's tools allow you to build indexed chains around user verification. A query can trigger `list_sender_ids` and then use that output to verify a user via `verify_otp`. LlamaIndex captures this entire successful sequence. This means every piece of data—from the list of IDs to the final success status—is added to your searchable index for future reference.

Setup guide

Set up Termii 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 Termii 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 Termii tools.",
)
response = await agent.run("List recent Termii data")

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Common questions about Termii MCP in LlamaIndex

LlamaIndex treats the MCP Server's tools as source data. You don't just call them; you index their results, allowing your application to query historical communication records and configurations.

Yes. The `send_whatsapp` tool output is indexed alongside SMS data. This lets you build a unified view of all multi-channel interactions for any user or region.

The server handles authentication records (OTP codes), financial status (`check_balance`), and sender identification. These are the core data points that get indexed into your vector store.

Definitely. By indexing every tool call, including `send_sms` or `send_whatsapp`, you build a detailed record of who was contacted, when, and through which channel.

The structure guarantees that every tool's output is verifiable. You get grounded answers from your knowledge base, eliminating hallucinations based on actual API responses.

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