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 LlamaIndex 2 tools — connect in under 2 minutes

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

docs.llamaindex.ai/en/stable/module_guides/tools/mcp

Built by Vinkius GDPR 2 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add QWeather Ocean/Tide API as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

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python

import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to QWeather Ocean/Tide API. "
            "You have 2 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in QWeather Ocean/Tide API?"
    )
    print(response)

asyncio.run(main())

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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.

LlamaIndex agents combine QWeather Ocean/Tide API tool responses with indexed documents for comprehensive, grounded answers. Connect 2 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

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 LlamaIndex 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 LlamaIndex via MCP

Follow these steps to integrate the QWeather Ocean/Tide API MCP Server with LlamaIndex.

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 2 tools from QWeather Ocean/Tide API

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

LlamaIndex provides unique advantages when paired with QWeather Ocean/Tide API through the Model Context Protocol.

Data-first architecture: LlamaIndex agents combine QWeather Ocean/Tide API tool responses with indexed documents for comprehensive, grounded answers

Query pipeline framework lets you chain QWeather Ocean/Tide API tool calls with transformations, filters, and re-rankers in a typed pipeline

Multi-source reasoning: agents can query QWeather Ocean/Tide API, a vector store, and a SQL database in a single turn and synthesize results

Observability integrations show exactly what QWeather Ocean/Tide API tools were called, what data was returned, and how it influenced the final answer

QWeather Ocean/Tide API + LlamaIndex Use Cases

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

Hybrid search: combine QWeather Ocean/Tide API real-time data with embedded document indexes for answers that are both current and comprehensive

Data enrichment: query QWeather Ocean/Tide API to augment indexed data with live information before generating user-facing responses

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying QWeather Ocean/Tide API for fresh data

Analytical workflows: chain QWeather Ocean/Tide API queries with LlamaIndex's data connectors to build multi-source analytical reports

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

These 2 tools become available when you connect QWeather Ocean/Tide API to LlamaIndex 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 LlamaIndex

Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex

Common issues when connecting QWeather Ocean/Tide API to LlamaIndex through the Vinkius, and how to resolve them.

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

QWeather Ocean/Tide API + LlamaIndex FAQ

Common questions about integrating QWeather Ocean/Tide API MCP Server with LlamaIndex.

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query QWeather Ocean/Tide API tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.