OpenWeatherMap MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Direct Geocoding, Get Air Pollution, Get Current Weather, and more

Name: OpenWeatherMap
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

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LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add OpenWeatherMap 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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The OpenWeatherMap MCP Server for LlamaIndex is a standout in the Data Analytics category — giving your AI agent 6 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 OpenWeatherMap. "
            "You have 6 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in OpenWeatherMap?"
    )
    print(response)

asyncio.run(main())

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About OpenWeatherMap MCP Server

Connect OpenWeatherMap to your AI agent to get instant access to global meteorological data. Whether you're planning travel, monitoring environmental conditions, or building weather-aware automations, this server provides the precise data you need.

LlamaIndex agents combine OpenWeatherMap 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

Current Conditions — Get live temperature, humidity, wind speed, and weather descriptions for any city or coordinate via get_current_weather.
Extended Forecasts — Access 5-day/3-hour forecasts with get_forecast or use the One Call 3.0 API for 48-hour hourly and 8-day daily projections via get_onecall.
Air Quality Monitoring — Retrieve real-time pollution data including PM2.5, PM10, CO, and Ozone levels using get_air_pollution.
Geocoding Services — Seamlessly convert city names to coordinates with direct_geocoding and vice versa with reverse_geocoding to power location-based queries.

The OpenWeatherMap MCP Server exposes 6 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 6 OpenWeatherMap tools available for LlamaIndex

When LlamaIndex connects to OpenWeatherMap through Vinkius, your AI agent gets direct access to every tool listed below — spanning meteorology, weather-forecast, air-quality, 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.

direct

Direct geocoding on OpenWeatherMap

Convert city names or zip codes into coordinates

get

Get air pollution on OpenWeatherMap

5, PM10, and NH3. Get current air pollution data

get

Get current weather on OpenWeatherMap

Get current weather data

get

Get forecast on OpenWeatherMap

Get 5 Day / 3 Hour Forecast

get

Get onecall on OpenWeatherMap

Get One Call API 3.0 weather data

reverse

Reverse geocoding on OpenWeatherMap

Convert coordinates into city names

Connect OpenWeatherMap to LlamaIndex via MCP

Follow these steps to wire OpenWeatherMap into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

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 6 tools from OpenWeatherMap

Why Use LlamaIndex with the OpenWeatherMap MCP Server

LlamaIndex provides unique advantages when paired with OpenWeatherMap through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine OpenWeatherMap tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain OpenWeatherMap tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query OpenWeatherMap, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what OpenWeatherMap tools were called, what data was returned, and how it influenced the final answer

OpenWeatherMap + LlamaIndex Use Cases

Practical scenarios where LlamaIndex combined with the OpenWeatherMap MCP Server delivers measurable value.

Hybrid search: combine OpenWeatherMap real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query OpenWeatherMap 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 OpenWeatherMap for fresh data

Analytical workflows: chain OpenWeatherMap queries with LlamaIndex's data connectors to build multi-source analytical reports

Example Prompts for OpenWeatherMap in LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with OpenWeatherMap immediately.

"What's the current weather in London?"

"Give me the 5-day forecast for Tokyo."

"Check the air pollution levels at latitude 40.71 and longitude -74.00."

Troubleshooting OpenWeatherMap MCP Server with LlamaIndex

Common issues when connecting OpenWeatherMap to LlamaIndex through Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

OpenWeatherMap + LlamaIndex FAQ

Common questions about integrating OpenWeatherMap MCP Server with LlamaIndex.

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.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query OpenWeatherMap tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.