NumVerify MCP Server for LlamaIndex 4 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add NumVerify as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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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 NumVerify. "
"You have 4 tools available."
),
)
response = await agent.run(
"What tools are available in NumVerify?"
)
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 NumVerify MCP Server
Empower your AI agent to orchestrate your entire phone validation and identity verification workflow with NumVerify, the global API for phone number intelligence. By connecting NumVerify to your agent, you transform complex validation tasks into a natural conversation. Your agent can instantly verify if a number is valid, audit carrier information, and retrieve geographic location data without you ever touching a manual lookup tool. Whether you are cleaning lead lists or verifying user identity, your agent acts as a real-time communications analyst, ensuring your phone data is always verified and accurate.
LlamaIndex agents combine NumVerify tool responses with indexed documents for comprehensive, grounded answers. Connect 4 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
- Phone Auditing — Verify if any international phone number is valid and retrieve detailed metadata, including country and dial codes.
- Carrier Oversight — Identify the current carrier for a phone number to maintain a clear view of network distribution.
- Location Discovery — Retrieve the geographic location (city/region) associated with a phone number instantly.
- Line-type Intelligence — Identify if a number is a mobile, landline, or VoIP line to optimize your communication strategy.
- Metadata Integrity — Retrieve official country names and formatting details to maintain strict organizational control over your contact data.
The NumVerify MCP Server exposes 4 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 NumVerify to LlamaIndex via MCP
Follow these steps to integrate the NumVerify 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 4 tools from NumVerify
Why Use LlamaIndex with the NumVerify MCP Server
LlamaIndex provides unique advantages when paired with NumVerify through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine NumVerify tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain NumVerify tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query NumVerify, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what NumVerify tools were called, what data was returned, and how it influenced the final answer
NumVerify + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the NumVerify MCP Server delivers measurable value.
Hybrid search: combine NumVerify real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query NumVerify 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 NumVerify for fresh data
Analytical workflows: chain NumVerify queries with LlamaIndex's data connectors to build multi-source analytical reports
NumVerify MCP Tools for LlamaIndex (4)
These 4 tools become available when you connect NumVerify to LlamaIndex via MCP:
get_phone_carrier
Get carrier information for a phone number
get_phone_line_type
Identify if a phone number is mobile, landline, or other
get_phone_location
Get geographic location details for a phone number
validate_phone
Verify if a phone number is valid and retrieve metadata
Example Prompts for NumVerify in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with NumVerify immediately.
"Validate the phone number +14158586273 using NumVerify."
"Identify the carrier for +442071838750."
"Check if +5511999999999 is a mobile line."
Troubleshooting NumVerify MCP Server with LlamaIndex
Common issues when connecting NumVerify to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpNumVerify + LlamaIndex FAQ
Common questions about integrating NumVerify 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 NumVerify 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 NumVerify to LlamaIndex
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.