Termii MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Check Balance, List Sender Ids, Send Otp, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Termii 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 Termii app connector for LlamaIndex is a standout in the Communication Messaging category — giving your AI agent 6 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 Termii. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in Termii?"
)
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 Termii MCP Server
Connect your Termii account to any AI agent and simplify how you manage your global messaging, secure verification, and multi-channel engagement through natural conversation.
LlamaIndex agents combine Termii tool responses with indexed documents for comprehensive, grounded answers. Connect 6 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
- Multi-channel Messaging — Send standard SMS and WhatsApp messages to recipients worldwide with reliable delivery tracking.
- Secure Verification (OTP) — Send and verify one-time passwords (OTP) programmatically to secure your user onboarding and transactions.
- Sender ID Management — List all registered Sender IDs to ensure your messages are delivered with recognized branding.
- Financial Monitoring — Check your account balance and track credit usage for your messaging campaigns directly from the agent.
- Global Coverage — Reach users across different channels (SMS, WhatsApp, Voice) using Termii's unified communication infrastructure.
- Real-time Oversight — Monitor transaction statuses and verify identity tokens instantly via AI commands.
The Termii MCP Server exposes 6 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 6 Termii tools available for LlamaIndex
When LlamaIndex connects to Termii through Vinkius, your AI agent gets direct access to every tool listed below — spanning multi-channel-messaging, otp-verification, whatsapp-business, 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.
Check account balance
List all registered Sender IDs
Pass options in JSON. Send a one-time password
Pass data as a JSON string. Send an SMS message
Pass data as a JSON string. Send a WhatsApp message
Verify an OTP code
Connect Termii to LlamaIndex via MCP
Follow these steps to wire Termii 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 Termii MCP Server
LlamaIndex provides unique advantages when paired with Termii through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Termii tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Termii tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Termii, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Termii tools were called, what data was returned, and how it influenced the final answer
Termii + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Termii MCP Server delivers measurable value.
Hybrid search: combine Termii real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Termii 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 Termii for fresh data
Analytical workflows: chain Termii queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Termii in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Termii immediately.
"Send a verification code (OTP) to +15550199."
"Check my account balance."
"List all Sender IDs registered for my account."
Troubleshooting Termii MCP Server with LlamaIndex
Common issues when connecting Termii to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTermii + LlamaIndex FAQ
Common questions about integrating Termii MCP Server with LlamaIndex.