How do I find my QWeather API Key?

Log in to your [**QWeather Developer portal**](https://dev.qweather.com/), create a project, and you will find your API Key in your dashboard. Copy and paste it below.

Does it support coordinate search?

Yes. You can provide location coordinates (lat,lon) to the `get_ocean_tide_data` tool to retrieve precise regional tide metadata.

What data format is returned for tide tables?

The API returns detailed hourly or daily tide tables, including timestamped water height and peak type metadata.

QWeather Ocean/Tide API MCP Server for CrewAI 2 tools — connect in under 2 minutes

Name: QWeather Ocean/Tide API
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 2 Tools Framework

Connect your CrewAI agents to QWeather Ocean/Tide API through Vinkius, pass the Edge URL in the `mcps` parameter and every QWeather Ocean/Tide 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="QWeather Ocean/Tide API Specialist",
    goal="Help users interact with QWeather Ocean/Tide API effectively",
    backstory=(
        "You are an expert at leveraging QWeather Ocean/Tide 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 QWeather Ocean/Tide API "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 2 available tools "
        "and what they can do."
    ),
)

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

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About QWeather Ocean/Tide API MCP Server

Empower your AI agent to orchestrate your entire maritime research and oceanographic auditing workflow with the QWeather Ocean/Tide API, the specialized source for global tide data. By connecting QWeather's ocean intelligence to your agent, you transform complex water level searches into a natural conversation. Your agent can instantly retrieve real-time tide tables, audit high and low water peaks, and query specific location metadata without you ever touching a technical portal. Whether you are planning coastal logistics or conducting marine research, your agent acts as a real-time oceanographic consultant, ensuring your data is always verified and precise.

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

Tide Auditing — Retrieve high-resolution tide tables for global locations and maintain a clear view of water level changes.
Peak Oversight — Audit high and low water times and heights to understand the temporal distribution of maritime scale instantly.
Geographic Discovery — Query tide data by location ID or coordinates to maintain strict organizational control over regional data.
Ocean Intelligence — Retrieve detailed oceanographic metadata to assist in deep-dive coastal classification.
Operational Monitoring — Check API status to ensure your maritime research workflow is always operational.

The QWeather Ocean/Tide API MCP Server exposes 2 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 Ocean/Tide API to CrewAI via MCP

Follow these steps to integrate the QWeather Ocean/Tide 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 2 tools from QWeather Ocean/Tide API

Why Use CrewAI with the QWeather Ocean/Tide API MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with QWeather Ocean/Tide 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

QWeather Ocean/Tide API + CrewAI Use Cases

Practical scenarios where CrewAI combined with the QWeather Ocean/Tide API MCP Server delivers measurable value.

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

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

QWeather Ocean/Tide API MCP Tools for CrewAI (2)

These 2 tools become available when you connect QWeather Ocean/Tide API to CrewAI via MCP:

check_api_status

Check if the QWeather Ocean service is operational

get_ocean_tide_data

Get real-time tide data for a specific location and date

Example Prompts for QWeather Ocean/Tide API in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with QWeather Ocean/Tide API immediately.

"Get tide data for location '101010100' (Shanghai) for '20240510' using QWeather."

"What is the tide forecast for latitude 22.3193 and longitude 114.1694 (Hong Kong)?"

"Show the full tide table for today."

Troubleshooting QWeather Ocean/Tide API MCP Server with CrewAI

Common issues when connecting QWeather Ocean/Tide 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.

QWeather Ocean/Tide API + CrewAI FAQ

Common questions about integrating QWeather Ocean/Tide 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.