| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Fetches 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.
Unique: 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.
vs alternatives: 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
Retrieves 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.
Unique: 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.
vs alternatives: 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
Exposes 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.
Unique: 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.
vs alternatives: 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
Enables 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.
Unique: 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.
vs alternatives: 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
Normalizes 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.
Unique: 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.
vs alternatives: Provides schema abstraction vs. exposing raw provider responses; enables future provider switching without agent code changes vs. tightly-coupled provider-specific integrations
Executes SQL queries against Supabase PostgreSQL instances through the Model Context Protocol, translating natural language or structured query requests into parameterized SQL statements. Uses MCP's tool-calling interface to expose database operations as callable functions with schema validation, enabling LLM agents to perform CRUD operations, joins, and aggregations with automatic connection pooling and credential management through Supabase client SDK.
Unique: Exposes Supabase PostgreSQL as MCP tools with automatic credential injection from Supabase client SDK, eliminating manual connection string management and enabling seamless LLM-to-database queries within Claude or compatible agents
vs alternatives: Tighter integration than generic SQL MCP servers because it leverages Supabase's built-in authentication and connection pooling rather than requiring separate database credential configuration
Exposes Supabase Auth session state and user metadata through MCP tools, allowing agents to inspect current authentication context, retrieve user profiles, and trigger auth-related operations. Integrates with Supabase's JWT-based auth system to validate sessions and access user claims without re-authenticating, using the Supabase client's built-in session management.
Unique: Integrates Supabase's JWT-based auth system directly into MCP tool interface, allowing agents to inspect and act on auth state without managing separate credential stores or re-authentication flows
vs alternatives: More seamless than generic auth MCP servers because it leverages Supabase's built-in session management and avoids redundant credential passing between agent and auth system
Invokes Supabase Edge Functions (serverless TypeScript/JavaScript functions) through MCP tools, passing parameters and receiving results with optional streaming support. Uses Supabase's edge function HTTP API to trigger functions with automatic authentication headers and response parsing, enabling agents to execute custom business logic without embedding it in the agent itself.
Supabase scores higher at 42/100 vs KnowAir Weather at 23/100.
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Unique: Exposes Supabase Edge Functions as MCP tools with automatic authentication and response parsing, allowing agents to invoke custom serverless logic without managing HTTP clients or credential injection
vs alternatives: More integrated than generic HTTP MCP tools because it handles Supabase-specific authentication, error handling, and response formatting automatically
Subscribes to real-time changes on Supabase tables through MCP's event streaming interface, using Supabase's PostgreSQL LISTEN/NOTIFY mechanism to push INSERT, UPDATE, and DELETE events to agents. Maintains persistent WebSocket connections and filters events by table and row-level policies, enabling agents to react to database changes without polling.
Unique: Bridges Supabase's PostgreSQL LISTEN/NOTIFY real-time system with MCP's tool interface, enabling agents to subscribe to database changes without managing WebSocket connections or event serialization
vs alternatives: More efficient than polling-based approaches because it uses Supabase's native real-time infrastructure rather than repeated database queries
Manages files in Supabase Storage buckets through MCP tools, supporting upload, download, list, and delete operations with automatic authentication and path-based access control. Uses Supabase's S3-compatible storage API with built-in support for public/private buckets and signed URLs for temporary access, enabling agents to handle file I/O without managing cloud storage credentials.
Unique: Exposes Supabase Storage's S3-compatible API as MCP tools with automatic authentication and signed URL generation, eliminating the need for agents to manage cloud storage credentials or generate temporary access tokens
vs alternatives: More integrated than generic S3 MCP tools because it leverages Supabase's built-in bucket policies and authentication rather than requiring separate AWS credentials
Performs semantic similarity searches on vector embeddings stored in Supabase PostgreSQL using pgvector extension, translating natural language queries into embedding vectors and executing cosine/L2 distance searches. Integrates with embedding providers (OpenAI, Cohere) or uses pre-computed embeddings, enabling agents to retrieve semantically similar documents or records without full-text search limitations.
Unique: Integrates pgvector directly into MCP tools with automatic embedding generation and distance calculation, enabling agents to perform semantic search without managing separate vector database infrastructure
vs alternatives: More efficient than external vector databases (Pinecone, Weaviate) for Supabase users because it colocates embeddings with relational data, reducing network latency and simplifying data synchronization
Exposes Supabase database schema information through MCP tools, allowing agents to discover table structures, column types, constraints, and relationships without manual schema documentation. Queries PostgreSQL information_schema and Supabase metadata tables to dynamically generate schema descriptions, enabling agents to construct valid queries and understand data relationships.
Unique: Queries Supabase's PostgreSQL information_schema directly through MCP tools, enabling agents to dynamically discover and adapt to database schemas without pre-configured schema definitions
vs alternatives: More flexible than static schema definitions because it reflects live database state, including recent migrations or schema changes
Enforces Supabase Row-Level Security policies within agent queries, ensuring that agents can only access rows permitted by RLS rules defined in the database. Evaluates policies based on authenticated user context (JWT claims, user ID) and applies WHERE clause filters automatically, preventing unauthorized data access at the database layer rather than application layer.
Unique: Delegates authorization enforcement to PostgreSQL RLS policies rather than implementing authorization in agent code, ensuring that data access rules are centralized and cannot be bypassed by agent logic
vs alternatives: More secure than application-level authorization because RLS is enforced at the database layer, preventing accidental data leaks even if agent code has bugs
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