How to Use the Xweather Renewable MCP in LlamaIndex

Q: Can LlamaIndex handle wind farm site assessments?

Yes. You can run getwinddata and then index those metrics alongside your operational documents. This creates a searchable knowledge base for turbine performance analysis.

Build knowledge bases around Xweather Renewable data using LlamaIndex.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Xweather Renewable MCP to LlamaIndex

Create your Vinkius account to connect Xweather Renewable 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.

GDPR Free for Subscribers

Setup Xweather Renewable with LlamaIndex

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Building a Knowledge Index with MCP Server

LlamaIndex indexes the output of `get_renewable_energy_farm_data` into a vector store. Instead of just getting a raw data dump, you can query that historical energy generation forecast later on. You're building a knowledge base grounded in actual API results. This means if you need to know what the average 5-minute interval production estimate was last quarter, your agent doesn't hallucinate it—it pulls the answer from the indexed data.

Solar Assessment for Xweather Renewable

Use `get_solar_irradiance_data` and index those historical values. This allows you to combine that raw solar input with site documentation, creating a unified knowledge resource. Your agent can then answer questions like: 'Given the site's elevation and this irradiance data, what was our expected yield?' The tool output becomes part of your searchable context. You don't just get numbers; you get answers synthesized from those numbers.

Tracking Severe Weather with LlamaIndex

When `get_weather_alerts` fires, index the advisory details immediately. This allows future queries to reference specific severe weather events and their impacts on your operations. The system retains context across sessions. This is huge for compliance reporting. You can query past incidents—say, 'What were the alerts recorded at Station ID 123 last fall?'—and get a grounded answer directly from the MCP Server's data.

Setup guide

Set up Xweather Renewable 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 Xweather Renewable 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 Xweather Renewable tools.",
)
response = await agent.run("List recent Xweather Renewable data")

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Vaisala Xweather. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Xweather Renewable now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Xweather Renewable MCP in LlamaIndex

It indexes all your weather forecast and energy production data. When you ask a complex question, it searches the stored API results to ground its answer, so you always know exactly which piece of data was used.

Yes. You can run `get_wind_data` and then index those metrics alongside your operational documents. This creates a searchable knowledge base for turbine performance analysis.

The server touches location metadata, including coordinates (lat/lon), observed weather conditions, and energy generation forecasts. All of this is indexed into your searchable knowledge base.

It's built for it. You simply pass the MCP tools to the FunctionAgent. The framework handles turning raw API data into structured, queryable knowledge.

You run a query against the indexed results. Instead of calling the tool again, you ask a question—like 'What was my yield last month?'—and the index pulls the answer from stored historical API calls.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript