SolarAnywhere API MCP for AI. Audit Site Viability with Real-Time Irradiance Data

Q: How do I check if the SolarAnywhere API is working before querying site data?

Run checkapistatus. This tool confirms the entire service pipeline's health. If it returns a 'failed' status, you know immediately that any subsequent query using other tools will fail too.

Q: Can I use listsolarsites to find coordinates for an old project?

Yes. listsolarsites provides the manifest of all registered sites in your account, giving you the asset metadata and coordinate data necessary to run other queries.

Q: How can I use listsolarsites results with getsolarirradiance?

Your agent first calls listsolarsites to pull the site catalog. Then, it takes the coordinates from that list and feeds them directly into getsolarirradiance for real-time performance checks.

Q: When should I use gettypicalsolaryear instead of checking live conditions?

Use gettypicalsolaryear when planning long-term feasibility or needing monthly averages. This provides historical context, whereas getsolarirradiance gives you what's happening right now.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

Connect to your AI in seconds.

SolarAnywhere API connects your AI agent directly to high-resolution solar irradiance data and site metadata. Use this server to check real-time Global Horizontal Irradiance (GHI) levels, audit Typical Meteorological Year (TMY) patterns for long-term potential, or list all registered sites in your catalog.

It turns complex meteorological searches into simple natural language queries for photovoltaic planning.

What your AI can do

Check api status

Verifies if the SolarAnywhere service is currently online and operational for data queries.

Get solar irradiance

Retrieves real-time Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) readings using coordinate pairs.

Get typical solar year

Calculates Typical Meteorological Year (TMY) solar data to estimate the long-term energy potential for a specific location.

+ 1 more capabilities included

Get real-time solar resource metrics

Use get_solar_irradiance to fetch current Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) readings for specific coordinates.

Model long-term solar potential

Run get_typical_solar_year to analyze Typical Meteorological Year (TMY) data, which assesses the expected annual performance of a site.

Audit registered project sites

Execute list_solar_sites to pull an updated manifest of every solar asset currently tracked in your SolarAnywhere account.

Check service operational status

Run check_api_status to confirm that the entire solar data pipeline is online and ready for use.

Ask an AI about this

Included with Plan

Waiting for input…

AI Agent

SolarAnywhere API: 4 Tools for Solar Data Analysis

These tools let your AI client run specific solar queries—checking status, getting live irradiance, modeling yearly data, and listing assets.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using SolarAnywhere API on Vinkius

Check Api Status

Verifies if the SolarAnywhere service is currently online and operational for data queries.

Get Solar Irradiance

Retrieves real-time Global Horizontal Irradiance (GHI) and Direct Normal Irradiance...

Get Typical Solar Year

Calculates Typical Meteorological Year (TMY) solar data to estimate the long-term...

List Solar Sites

Returns a complete list of all registered solar sites and their metadata stored in...

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The SolarAnywhere API integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "solaranywhere-api": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the SolarAnywhere API tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"solaranywhere-api": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with SolarAnywhere API, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,100+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

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

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Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

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EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Works with Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 4 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Manual solar data gathering takes forever.

Today, assessing a new site means logging into the meteorological service portal. You search by coordinates, then you select the correct time range (e.g., 20-year average), and finally, you download a massive spreadsheet containing GHI, DNI, and temperature metrics. It takes fifteen minutes of clicking through tabs just to get basic numbers.

With this MCP server, your AI agent handles it all. You tell it the coordinates and the data type (e.g., 'Get TMY for this location'). The agent executes `get_typical_solar_year` and returns the structured data you need—no portals, no downloads, just clean metrics.

SolarAnywhere API MCP Server: Get real-time irradiance data.

Before this server, checking current site performance meant calling an external service and waiting for a manual readout. If the local conditions changed, you had to repeat the process entirely—a huge time sink for operations teams.

Now, running `get_solar_irradiance` is instant. You ask your agent for real-time data, and it delivers the GHI and DNI values immediately. It's a single prompt that replaces multiple manual data pulls.

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What your AI can actually do with this

This API gives your agent direct access to high-resolution solar irradiance data and site metadata from SolarAnywhere. You're building out a photovoltaic planning system, and this server handles the complex meteorological searches so you don't have to touch any technical portals. Your AI client uses four specific tools to give you full control over site auditing and energy research.

First, you can confirm connectivity by running check_api_status. This simply verifies that the entire solar data pipeline is online and ready for actual queries. Next, when you need current metrics, use get_solar_irradiance to pull real-time Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) readings. You just feed it a pair of coordinates, and it spits out the immediate energy density data for that spot.

For long-term planning, you'll run get_typical_solar_year. This tool doesn't give you today's numbers; instead, it calculates Typical Meteorological Year (TMY) solar data. TMY is how experts estimate a site's expected annual performance by modeling historical conditions over an entire year—it's crucial for sizing equipment and forecasting long-term energy potential at any given location.

If you need to audit your existing assets, use list_solar_sites. This pulls a complete manifest of every solar asset registered in your account. It gives you all the site metadata associated with those projects, letting you keep an accurate inventory of everything tracked by SolarAnywhere. These functions—get_solar_irradiance, get_typical_solar_year, and list_solar_sites—let your agent work together: it can check operational status, pull real-time metrics for immediate decisions, model decades-long performance using TMY data, and maintain a running list of all project sites.

You're not just querying data; you're making complex solar intelligence accessible through simple natural language prompts.

Built · Hosted · Managed by Vinkius SolarAnywhere API - Solar Irradiance Data for AI Agents

Server ID 019d8483-0b05-7020-83c7-16170be56d6a

Vinkius Inspector

Compliance Grade A+

Score 100/100

Report View Report ↗

Here's how it actually works

The bottom line is: it lets your AI client act as a real-time solar consultant by running specialized queries against large meteorological datasets.

First, subscribe to this server on Vinkius and provide your unique SolarAnywhere API Key.

Next, tell your AI client the task (e.g., 'Check GHI for coordinates X, Y').

The agent executes the necessary tool call (get_solar_irradiance) and returns the structured solar data directly to you.

Who is this actually for?

Solar Engineers and Renewable Energy Developers use this when they're tired of switching between GIS software, proprietary portals, and spreadsheets just to check if a site is viable. They need precise, immediate data—real-time irradiance or TMY averages—to prove ROI before spending millions on development.

Solar Engineer

Uses get_solar_irradiance to validate site performance against current weather conditions and checks the API status using check_api_status.

Renewable Energy Developer

Runs get_typical_solar_year on candidate locations to model long-term energy yields, comparing potential across multiple sites listed via list_solar_sites.

Sustainability Lead

Asks the agent general questions about regional solar assets and pulls reports using natural language prompts that trigger site audits or irradiance checks.

What Changes When You Connect

Get instant, accurate irradiance data. Instead of manually inputting coordinates into a web portal and waiting for the chart to load, simply ask your agent to run get_solar_irradiance and get GHI/DNI numbers immediately.

Model long-term performance with TMY data. You don't have to guess at annual output. Use get_typical_solar_year to baseline solar potential for a site, which is critical for investor reports.

Keep track of your assets in one place. Running list_solar_sites gives you an immediate manifest of every registered project location without having to navigate complex account dashboards.

Verify data integrity first. Before running any major analysis, check the system health by calling check_api_status. This confirms the underlying solar data pipeline is functional and reliable.

Automate cross-checks. You can combine tools—for instance, using list_solar_sites to get a list of coordinates, then feeding those into get_solar_irradiance for immediate real-time checks across the whole portfolio.

See it in action

01 01

Evaluating an unlisted candidate site

A developer finds a potential site but has never logged it into their system. They ask their agent to 'Check solar potential for these coordinates.' The agent runs get_solar_irradiance and immediately delivers the real-time GHI and DNI metrics, allowing an instant go/no-go decision without manual data fetching.

02 02

Auditing a regional fleet

An operations lead needs to report on 50 different installed solar assets. They first use list_solar_sites to get the coordinates, then they feed that list into the agent which runs targeted queries using get_solar_irradiance across all of them for a single dashboard view.

03 03

Comparing historical vs. current data

A project manager needs to know if a site's current output is normal. They run get_typical_solar_year for the long-term baseline, and then use get_solar_irradiance to compare that against today's real-time metrics. This gives them immediate variance reporting.

04 04

Debugging a data pipeline failure

The team runs an analysis and gets garbage data. Before starting the full query, they first call check_api_status. If the status is 'Operational,' they know the problem lies in their input parameters, not the service itself.

The honest tradeoffs

Assuming site data is always current

Anti-pattern

Running an analysis using only get_typical_solar_year and assuming that long-term averages predict today's performance. This misses immediate weather fluctuations.

The Fix

Always complement TMY planning with a real-time check. After running get_typical_solar_year, follow up by calling get_solar_irradiance to validate the current, actual resource availability.

Ignoring system health checks

Anti-pattern

Trying to pull data using list_solar_sites and failing due to a temporary API outage. You waste time troubleshooting bad inputs.

The Fix

Always start with a simple check_api_status. If the status check fails, you know immediately that the issue is external or system-wide, saving time.

Mixing up asset lists and raw data

Anti-pattern

Using list_solar_sites to get coordinates, but then trying to run a query without specifying which site's metadata you want. The tool can't guess your intent.

The Fix

After running list_solar_sites, reference the returned asset ID or name in your subsequent calls to ensure the agent knows exactly which resource pool to analyze.

When It Fits, When It Doesn't

Use this server if your core need is validating solar energy resources—specifically irradiance metrics, long-term potential (TMY), or managing an existing catalog of physical assets. The tools are perfect for initial site screening and technical feasibility studies.

Don't use it if your problem involves financial modeling, tax code compliance, or grid interconnection costs. These require external data sources (like utility rate databases) that this API doesn't provide. For instance, while get_solar_irradiance gives you W/m², it won't tell you the cost to connect those watts to the grid.

If your workflow needs both resource data and a way to track physical assets, run list_solar_sites first. If you just need to validate if the system is working before anything else, start with check_api_status. It's fundamentally a technical auditing tool.

Questions you might have

How do I check if the SolarAnywhere API is working before querying site data? +

Run check_api_status. This tool confirms the entire service pipeline's health. If it returns a 'failed' status, you know immediately that any subsequent query using other tools will fail too.

Can I use list_solar_sites to find coordinates for an old project? +

Yes. list_solar_sites provides the manifest of all registered sites in your account, giving you the asset metadata and coordinate data necessary to run other queries.

What's the difference between get_solar_irradiance and get_typical_solar_year? +

Irradiance is real-time (current day) data, giving you immediate metrics. TMY uses historical averages to predict long-term energy potential for a site.

Do I need an API key every time I run get_solar_irradiance? +

The server handles the authentication using the API Key you provide during setup. You just have to include the coordinates in your prompt; the agent manages the key.

What format does get_solar_irradiance require for latitude and longitude? +

It needs both coordinates in standard decimal degree format. You must provide the precise latitude and longitude pairs to get real-time data for a specific spot.

How can I use list_solar_sites results with get_solar_irradiance? +

Your agent first calls list_solar_sites to pull the site catalog. Then, it takes the coordinates from that list and feeds them directly into get_solar_irradiance for real-time performance checks.

Does get_solar_irradiance return temperature or only irradiance data? +

It returns more than just irradiance; it also pulls in relevant meteorological data like ambient temperature. This helps you assess the full operating environment for that location.

When should I use get_typical_solar_year instead of checking live conditions? +

Use get_typical_solar_year when planning long-term feasibility or needing monthly averages. This provides historical context, whereas get_solar_irradiance gives you what's happening right now.

How do I find my SolarAnywhere API Key? +

Log in to your SolarAnywhere account, and you will find your API Key in your dashboard or profile settings. Copy and paste it below.

What irradiance parameters are provided? +

The API provides Global Horizontal Irradiance (GHI), Direct Normal Irradiance (DNI), and Diffuse Horizontal Irradiance (DHI) metadata.

Can the agent show historical typical year data? +

Yes. The get_typical_solar_year tool retrieves TMY data for any coordinate pair to assist in long-term performance auditing.

Connect to your AI in seconds.

Check api status

Get solar irradiance

Get typical solar year

SolarAnywhere API: 4 Tools for Solar Data Analysis

Make your AI actually useful.

Check Api Status

Get Solar Irradiance

Get Typical Solar Year

List Solar Sites

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Works with Claude, ChatGPT, Cursor, and more

Manual solar data gathering takes forever.

SolarAnywhere API MCP Server: Get real-time irradiance data.

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

See it in action

Evaluating an unlisted candidate site

Auditing a regional fleet

Comparing historical vs. current data

Debugging a data pipeline failure

The honest tradeoffs

Assuming site data is always current

Ignoring system health checks

Mixing up asset lists and raw data

When It Fits, When It Doesn't

Questions you might have