How to Use the AT&T 5G MCP in LlamaIndex

Index live AT&T 5G network data and query it with your LlamaIndex RAG application.

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Connect AT&T 5G MCP to LlamaIndex

Create your Vinkius account to connect AT&T 5G 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 AT&T 5G with LlamaIndex

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Index Your Network State

Don't just call the API; index the results. Use this MCP Server to run tools like `get_network_slice_info` and `list_network_sessions` periodically. LlamaIndex will automatically ingest the output—SLA parameters, device lists, session data—into a vector store. Now you have a searchable history of your network's state. Instead of just getting a point-in-time snapshot, you can ask your RAG app questions like "What were the SLA parameters for the 'enterprise-main' slice last Tuesday?" and get an answer grounded in actual data.

Ground Security Alerts in Facts

Connect your LlamaIndex agent to the AT&T 5G tools. When a potential fraud alert comes in, the agent can call `check_sim_swap` and `get_device_location`. The results—days since last swap, approximate location—are indexed immediately. This creates a rich, queryable context for every security event. Your support team can then ask "Show me all users who had a SIM swap and a location change greater than 500 miles in the last 24 hours." LlamaIndex retrieves the indexed tool outputs, giving you a list of high-risk accounts.

Index and Query QoS Sessions

Your agent can use `request_quality_on_demand` to boost network performance for critical tasks. But with LlamaIndex, the session ID and profile (`low_latency`, `high_throughput`) are indexed for later analysis. You're building a log of every time you requested premium quality. This turns API calls into a business intelligence tool. You can query your index to find out "How many `low_latency` sessions did we use during the Q3 product launch?" or "Which device groups requested `high_throughput` the most?" This MCP provides the data; LlamaIndex makes it smart.

Setup guide

Set up AT&T 5G 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 AT&T 5G 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 AT&T 5G tools.",
)
response = await agent.run("List recent AT&T 5G 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 AT&T 5G. 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 AT&T 5G MCP in LlamaIndex

Yes, if you've indexed the output. Have your agent periodically call `get_network_slice_info` and ingest the results. LlamaIndex then lets you query that historical data to track changes or audit configurations.

Your agent calls the tool, and LlamaIndex ingests the location data (latitude, longitude) into its knowledge base, linking it to a user or event. You can then perform semantic searches like "find events near this location" that use the real API data.

LlamaIndex will index whatever the tool returns, which is a verification status and confidence score. You configure what gets stored. For security, you can have it index the event (e.g., 'user 123 verified at timestamp X') without storing the phone number itself in the vector index.

LlamaIndex is built to turn data into a queryable knowledge base. Using this MCP Server, the output from tools like `list_network_sessions` isn't just a one-off response; it's automatically structured and indexed, ready to be used in a RAG application.

Vinkius isolates each MCP server call. When your LlamaIndex agent calls `get_device_location`, the request is handled in a temporary, secure environment that is destroyed after the location data is returned. The data doesn't persist on the Vinkius server.

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