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NWS (National Weather Service) MCP Server for LlamaIndexGive LlamaIndex instant access to 9 tools to Get Active Alerts, Get Active Alerts By Area, Get Alert, and more

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add NWS (National Weather Service) 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 for LlamaIndex

The NWS (National Weather Service) MCP Server for LlamaIndex is a standout in the Data Analytics category — giving your AI agent 9 tools to work with, ready to go from day one.

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python
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 NWS (National Weather Service). "
            "You have 9 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in NWS (National Weather Service)?"
    )
    print(response)

asyncio.run(main())
NWS (National Weather Service)
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 NWS (National Weather Service) MCP Server

Connect to the National Weather Service (NWS) API to retrieve precise meteorological data for any US location. This server allows AI agents to fetch point-based grid information, detailed textual forecasts, hourly updates, and critical weather alerts.

LlamaIndex agents combine NWS (National Weather Service) tool responses with indexed documents for comprehensive, grounded answers. Connect 9 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

  • Location Mapping — Convert coordinates into NWS grid points using get_point to unlock hyper-local data.
  • Forecasts — Get detailed textual and hourly forecasts for specific grid locations via get_forecast and get_hourly_forecast.
  • Weather Alerts — Monitor active watches, warnings, and advisories nationwide or by specific state/area with get_active_alerts and get_active_alerts_by_area.
  • Station Observations — Access real-time data from weather stations, including the latest atmospheric readings using get_latest_station_observation.

The NWS (National Weather Service) MCP Server exposes 9 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 9 NWS (National Weather Service) tools available for LlamaIndex

When LlamaIndex connects to NWS (National Weather Service) through Vinkius, your AI agent gets direct access to every tool listed below — spanning meteorological-data, weather-forecast, real-time-alerts, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

get

Get active alerts on NWS (National Weather Service)

Get all currently active weather alerts

get

Get active alerts by area on NWS (National Weather Service)

g., TX, FL, AMZ). Get active alerts for a specific area

get

Get alert on NWS (National Weather Service)

Get details for a specific weather alert

get

Get forecast on NWS (National Weather Service)

Get textual forecast for a specific grid location

get

Get hourly forecast on NWS (National Weather Service)

Get hourly forecast for a specific grid location

get

Get latest station observation on NWS (National Weather Service)

Get the latest observation for a specific station

get

Get point on NWS (National Weather Service)

Get NWS office and grid information for a latitude/longitude

get

Get station observations on NWS (National Weather Service)

Get observations for a specific station

get

Get stations on NWS (National Weather Service)

Get a list of all observation stations

Connect NWS (National Weather Service) to LlamaIndex via MCP

Follow these steps to wire NWS (National Weather Service) into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

01

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 9 tools from NWS (National Weather Service)

Why Use LlamaIndex with the NWS (National Weather Service) MCP Server

LlamaIndex provides unique advantages when paired with NWS (National Weather Service) through the Model Context Protocol.

01

Data-first architecture: LlamaIndex agents combine NWS (National Weather Service) tool responses with indexed documents for comprehensive, grounded answers

02

Query pipeline framework lets you chain NWS (National Weather Service) tool calls with transformations, filters, and re-rankers in a typed pipeline

03

Multi-source reasoning: agents can query NWS (National Weather Service), a vector store, and a SQL database in a single turn and synthesize results

04

Observability integrations show exactly what NWS (National Weather Service) tools were called, what data was returned, and how it influenced the final answer

NWS (National Weather Service) + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the NWS (National Weather Service) MCP Server delivers measurable value.

01

Hybrid search: combine NWS (National Weather Service) real-time data with embedded document indexes for answers that are both current and comprehensive

02

Data enrichment: query NWS (National Weather Service) to augment indexed data with live information before generating user-facing responses

03

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying NWS (National Weather Service) for fresh data

04

Analytical workflows: chain NWS (National Weather Service) queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for NWS (National Weather Service) in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with NWS (National Weather Service) immediately.

01

"What is the weather forecast for coordinates 34.0522, -118.2437?"

02

"Are there any active weather alerts in Texas right now?"

03

"Get the latest weather observation for station KLAX."

Troubleshooting NWS (National Weather Service) MCP Server with LlamaIndex

Common issues when connecting NWS (National Weather Service) to LlamaIndex through Vinkius, and how to resolve them.

01

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

NWS (National Weather Service) + LlamaIndex FAQ

Common questions about integrating NWS (National Weather Service) MCP Server with LlamaIndex.

01

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
02

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query NWS (National Weather Service) tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
03

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

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