KnowAir Weather
MCP ServerFree** – Real-time weather **and air quality** via the Caiyun Weather API (meteorology + AQI, CN & US standards).
Capabilities5 decomposed
real-time weather data retrieval with multi-standard support
Medium confidenceFetches current weather conditions and forecasts from the Caiyun Weather API, supporting both Chinese meteorological standards and international formats. The MCP server acts as a standardized interface layer that abstracts the Caiyun API's response schema, enabling LLM agents to query weather data through a unified protocol without direct API credential management or response parsing logic.
Implements MCP protocol as a standardized wrapper around Caiyun Weather API, enabling LLM agents to access weather data through tool-calling without credential exposure or response parsing boilerplate. Dual-standard support (CN + US) in a single interface differentiates it from region-locked weather tools.
Provides unified MCP interface for weather data vs. requiring agents to manage raw API calls to multiple weather providers; native support for both Chinese and US meteorological standards in one tool reduces integration complexity for multi-region applications
air quality index (aqi) monitoring with dual-standard reporting
Medium confidenceRetrieves real-time air quality metrics from Caiyun Weather API, translating raw pollutant concentrations (PM2.5, PM10, O3, NO2, SO2, CO) into both Chinese Environmental Quality Standards (EQS) and US EPA AQI scales. The MCP server normalizes these standards into a unified response schema, allowing agents to reason about air quality across regulatory frameworks without manual conversion logic.
Dual-standard AQI normalization (CN EQS + US EPA) in a single MCP tool eliminates the need for agents to manage separate API calls or manual standard conversions. Pollutant-level granularity (PM2.5, PM10, O3, NO2, SO2, CO) enables fine-grained health reasoning vs. simple index-only tools.
Provides both Chinese and US AQI standards in one tool vs. requiring separate integrations for each region; pollutant-level data enables more nuanced agent reasoning than index-only AQI tools
mcp protocol endpoint for weather and aqi tool calling
Medium confidenceExposes weather and AQI data retrieval as standardized MCP tools that LLM agents can discover and invoke through the Model Context Protocol. The server implements MCP's tool schema definition and response marshaling, allowing Claude and other MCP-compatible clients to call weather/AQI functions as first-class tools without custom integration code. Handles credential management server-side, so agents never see raw API keys.
Implements full MCP server lifecycle (tool registration, schema definition, request/response marshaling) for weather/AQI data, enabling seamless integration with Claude and other MCP clients. Server-side credential management prevents API key exposure to agents.
Native MCP implementation vs. custom tool-calling wrappers; eliminates need for agents to manage API credentials or response parsing; compatible with any MCP client vs. vendor-specific tool integrations
location-based weather and aqi context injection for agents
Medium confidenceEnables LLM agents to automatically enrich their reasoning context with real-time weather and air quality data for specified locations. The MCP server retrieves and formats weather/AQI data in a way that agents can incorporate into their decision-making without explicit tool invocation — data can be pre-fetched and injected into system prompts or retrieved on-demand as part of tool-calling workflows. Supports batch location queries for multi-region scenarios.
Bridges real-time environmental data and agent reasoning by providing both on-demand tool-calling and context pre-injection patterns. Batch query support reduces API overhead for multi-location scenarios vs. single-location-only tools.
Supports both tool-calling and context injection patterns vs. tools that only support one approach; batch location queries reduce API call overhead vs. per-location sequential queries
standardized weather data schema mapping across api providers
Medium confidenceNormalizes Caiyun Weather API responses into a consistent internal schema that abstracts provider-specific field names and data structures. The MCP server maps raw Caiyun fields (temperature, humidity, wind, precipitation) to standardized keys, enabling agents to work with weather data without learning provider-specific response formats. Schema includes both current conditions and forecast data with consistent temporal indexing.
Implements schema normalization layer that abstracts Caiyun API specifics, enabling agents to work with weather data through a provider-agnostic interface. Designed to support future multi-provider backends without agent-side changes.
Provides schema abstraction vs. exposing raw provider responses; enables future provider switching without agent code changes vs. tightly-coupled provider-specific integrations
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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Best For
- ✓LLM agents and AI applications requiring real-time weather context
- ✓Teams building weather-aware automation workflows in China and US markets
- ✓Developers integrating weather data into multi-modal reasoning systems
- ✓Health and wellness applications operating in China and US markets
- ✓Environmental monitoring agents and compliance systems
- ✓Multi-region logistics or delivery optimization systems that factor air quality into routing
- ✓Developers building Claude agents or other MCP-compatible LLM applications
- ✓Teams deploying local MCP servers for agent tool access without cloud dependencies
Known Limitations
- ⚠Depends on Caiyun Weather API availability and rate limits — no built-in caching or fallback providers
- ⚠Geographic coverage limited to regions supported by Caiyun (primarily China with US data available)
- ⚠No historical weather data or long-term trend analysis — only current conditions and near-term forecasts
- ⚠AQI data granularity depends on Caiyun's sensor network — sparse coverage in rural areas
- ⚠No historical AQI trends or predictive modeling — only current snapshot data
- ⚠Conversion between CN and US standards is approximate; regulatory compliance requires official source verification
Requirements
Input / Output
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** – Real-time weather **and air quality** via the Caiyun Weather API (meteorology + AQI, CN & US standards).
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