How do I find my SolarAnywhere API Key?

Log in to your [**SolarAnywhere account**](https://api.solaranywhere.com/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.

SolarAnywhere API MCP Server for CrewAI 4 tools — connect in under 2 minutes

Name: SolarAnywhere API
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 4 Tools Framework

Connect your CrewAI agents to SolarAnywhere API through Vinkius, pass the Edge URL in the `mcps` parameter and every SolarAnywhere API tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="SolarAnywhere API Specialist",
    goal="Help users interact with SolarAnywhere API effectively",
    backstory=(
        "You are an expert at leveraging SolarAnywhere API tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in SolarAnywhere API "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 4 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About SolarAnywhere API MCP Server

Empower your AI agent to orchestrate your entire solar energy research and site auditing workflow with SolarAnywhere, the authoritative source for high-resolution solar irradiance data. By connecting the SolarAnywhere API to your agent, you transform complex meteorological searches into a natural conversation. Your agent can instantly retrieve real-time irradiance levels, audit typical meteorological year (TMY) data, and query specific site metadata without you ever touching a technical portal. Whether you are conducting renewable energy research or managing regional solar fleet constraints, your agent acts as a real-time solar consultant, ensuring your data is always verified and precise.

When paired with CrewAI, SolarAnywhere API becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call SolarAnywhere API tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Irradiance Auditing — Retrieve real-time Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) data for any coordinate pair instantly.
Site Oversight — Audit all registered solar sites in your catalog to maintain a clear view of regional distribution and scale.
Weather Discovery — Query Typical Meteorological Year (TMY) data to understand long-term solar potential for your energy projects.
Atmospheric Intelligence — Retrieve temperature and irradiance metadata to assist in deep-dive solar performance classification.
Operational Monitoring — Check API status to ensure your solar research workflow is always operational.

The SolarAnywhere API MCP Server exposes 4 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect SolarAnywhere API to CrewAI via MCP

Follow these steps to integrate the SolarAnywhere API MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 4 tools from SolarAnywhere API

Why Use CrewAI with the SolarAnywhere API MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with SolarAnywhere API through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

SolarAnywhere API + CrewAI Use Cases

Practical scenarios where CrewAI combined with the SolarAnywhere API MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries SolarAnywhere API for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries SolarAnywhere API, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain SolarAnywhere API tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries SolarAnywhere API against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

SolarAnywhere API MCP Tools for CrewAI (4)

These 4 tools become available when you connect SolarAnywhere API to CrewAI via MCP:

check_api_status

Check if the SolarAnywhere service is operational

get_solar_irradiance

Get real-time solar irradiance data for a specific location

get_typical_solar_year

Get Typical Meteorological Year (TMY) solar data for a location

list_solar_sites

List all solar sites registered in your SolarAnywhere account

Example Prompts for SolarAnywhere API in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with SolarAnywhere API immediately.

"Get solar irradiance for latitude 34.0522 and longitude -118.2437 using SolarAnywhere."

"Show Typical Meteorological Year data for 'Napa Valley'."

"List all registered solar sites in my account."

Troubleshooting SolarAnywhere API MCP Server with CrewAI

Common issues when connecting SolarAnywhere API to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

SolarAnywhere API + CrewAI FAQ

Common questions about integrating SolarAnywhere API MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.