How do I find my QWeather API Key?

Log in to the [QWeather Developer Console](https://dev.qweather.com/), create a project, and your API Key will be displayed in the project settings. Ensure you select the correct key type (Web API).

What is the difference between dev and commercial plans?

The 'dev' plan uses `devapi.qweather.com` and has limited data frequency and locations. Commercial plans (standard/premium) use `api.qweather.com` and provide higher resolution data and broader global coverage. Set your `qweather_plan` in the credentials to use the correct endpoint.

Can I query weather by coordinates?

Yes! You can pass coordinates in the format `longitude,latitude` (e.g., '116.41,39.92') to any tool that accepts a `location` parameter.

QWeather / 和风天气 MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: QWeather / 和风天气
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

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ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="QWeather / 和风天气 Specialist",
    goal="Help users interact with QWeather / 和风天气 effectively",
    backstory=(
        "You are an expert at leveraging QWeather / 和风天气 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 QWeather / 和风天气 "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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About QWeather / 和风天气 MCP Server

Empower your AI agent to orchestrate your daily planning and environmental monitoring with QWeather (和风天气), the premier commercial weather platform in China. By connecting QWeather to your agent, you transform complex meteorological data and location-based environmental searches into a natural conversation. Your agent can instantly retrieve real-time weather, 15-day forecasts, air quality indices, severe weather warnings, and astronomical data without you ever needing to navigate a technical dashboard. Whether you are planning outdoor operations or auditing air quality across different regions, your agent acts as a real-time environmental consultant, providing accurate and fast results from a single, unified source.

When paired with CrewAI, QWeather / 和风天气 becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call QWeather / 和风天气 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

Weather Orchestration — Retrieve current weather and detailed forecasts (up to 15 days) for any location worldwide.
Air Quality Auditing — Monitor real-time AQI, PM2.5, and PM10 levels to ensure safe operating conditions.
Life Index Insights — Access specialized indices for UV radiation, clothing recommendations, and car washing suitability.
Warning Monitoring — Audit active severe weather warnings to maintain safety and organizational continuity.
Geographic Discovery — Search for location IDs and coordinates using keywords to refine your regional tracking.

The QWeather / 和风天气 MCP Server exposes 10 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 QWeather / 和风天气 to CrewAI via MCP

Follow these steps to integrate the QWeather / 和风天气 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 10 tools from QWeather / 和风天气

Why Use CrewAI with the QWeather / 和风天气 MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with QWeather / 和风天气 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

QWeather / 和风天气 + CrewAI Use Cases

Practical scenarios where CrewAI combined with the QWeather / 和风天气 MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries QWeather / 和风天气 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 QWeather / 和风天气, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain QWeather / 和风天气 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 QWeather / 和风天气 against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

QWeather / 和风天气 MCP Tools for CrewAI (10)

These 10 tools become available when you connect QWeather / 和风天气 to CrewAI via MCP:

get_air_now

5, etc.). Get current air quality

get_indices

Get daily life indices

get_moon_astronomy

Get moonrise and moonset times

get_sun_astronomy

Get sunrise and sunset times

get_warning

Get weather warnings

get_weather_24h

Get 24-hour weather forecast

get_weather_3d

Get 3-day weather forecast

get_weather_7d

Get 7-day weather forecast

get_weather_now

Get current weather

lookup_location

Search for location ID

Example Prompts for QWeather / 和风天气 in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with QWeather / 和风天气 immediately.

"What is the current weather in Beijing (101010100)?"

"Check the air quality for Shanghai today."

"Find the location ID for 'Hangzhou'."

Troubleshooting QWeather / 和风天气 MCP Server with CrewAI

Common issues when connecting QWeather / 和风天气 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.

QWeather / 和风天气 + CrewAI FAQ

Common questions about integrating QWeather / 和风天气 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.