Dexatel MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Dexatel 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
Vinkius supports streamable HTTP and SSE.
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 Dexatel. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in Dexatel?"
)
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 Dexatel MCP Server
Integrate Dexatel, the comprehensive cloud communications platform, directly into your AI workflow. Send SMS messages globally, monitor your messaging logs and delivery statuses, and manage your contact database using natural language.
LlamaIndex agents combine Dexatel 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
- Messaging Control — Send and receive SMS messages using your authorized Sender IDs and virtual numbers.
- Delivery Oversight — Monitor messaging logs in real-time, including technical delivery timestamps and carrier info.
- Contact Management — Access and manage your address book, including profiles and messaging history for specific contacts.
- Balance Monitoring — Track your account credit balance and API usage directly via chat.
The Dexatel MCP Server exposes 10 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.
How to Connect Dexatel to LlamaIndex via MCP
Follow these steps to integrate the Dexatel MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from Dexatel
Why Use LlamaIndex with the Dexatel MCP Server
LlamaIndex provides unique advantages when paired with Dexatel through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Dexatel tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Dexatel tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Dexatel, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Dexatel tools were called, what data was returned, and how it influenced the final answer
Dexatel + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Dexatel MCP Server delivers measurable value.
Hybrid search: combine Dexatel real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Dexatel 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 Dexatel for fresh data
Analytical workflows: chain Dexatel queries with LlamaIndex's data connectors to build multi-source analytical reports
Dexatel MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect Dexatel to LlamaIndex via MCP:
get_account_balance_metadata
Retrieve current balance and metadata for your Dexatel account
get_contact_profile
Get full profile and history for a specific contact
get_sms_message_details
Get detailed information for a specific SMS message
list_authorized_sender_ids
List all authorized Sender IDs and virtual numbers
list_failed_sms_deliveries
Identify SMS messages that failed to deliver (mock logic)
list_messaging_contacts
List all contacts stored in your Dexatel address book
list_sms_messages
List all sent and received SMS messages in your Dexatel account
list_sms_templates
List all approved message templates
search_sms_by_content
Search for SMS messages containing specific keywords or numbers
send_sms_message
Send a new SMS message to a specific number
Example Prompts for Dexatel in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Dexatel immediately.
"Send an SMS to '+1234567890' saying 'Your order is ready!'."
"Show me the last 5 sent messages."
"What is my current account balance?"
Troubleshooting Dexatel MCP Server with LlamaIndex
Common issues when connecting Dexatel to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpDexatel + LlamaIndex FAQ
Common questions about integrating Dexatel 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?
Connect Dexatel with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Dexatel to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.