| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability integrates real-time market data from various financial sources using WebSocket connections, allowing users to receive live updates on stock prices and market movements. It employs an event-driven architecture that ensures low latency and high throughput, making it distinct from traditional polling methods. The system can handle multiple data streams simultaneously, providing a comprehensive view of the market.
Unique: Utilizes WebSocket for real-time data streaming rather than HTTP polling, enabling faster updates and reduced latency.
vs alternatives: More efficient than traditional APIs that rely on polling, providing instant updates without the overhead.
This capability allows users to create and customize dashboards using a drag-and-drop interface, leveraging a component-based architecture. Users can select from various widgets that display different types of data, such as charts, tables, and indicators, and arrange them according to their preferences. This modular approach enables quick adjustments and personalized layouts.
Unique: Employs a component-based architecture that allows for real-time updates and reactivity in dashboard layouts, enhancing user experience.
vs alternatives: More flexible than static dashboards, enabling users to adapt their views on-the-fly without reloading.
This capability orchestrates API calls to multiple financial data providers, allowing users to aggregate data from various sources seamlessly. It uses a microservices architecture to manage different API integrations, ensuring that the system can scale and adapt to new providers easily. The orchestration layer handles authentication, rate limiting, and error management, providing a unified interface for users.
Unique: Features a microservices architecture that allows for easy addition of new data providers without disrupting existing functionality.
vs alternatives: More adaptable than monolithic systems, allowing for rapid integration of new APIs as needed.
This capability implements user authentication and session management using JWT (JSON Web Tokens) for secure access control. It ensures that user sessions are maintained across different components of the dashboard while providing mechanisms for token expiration and refresh. The architecture supports both single and multi-user environments, making it versatile for various use cases.
Unique: Utilizes JWT for stateless authentication, allowing for scalable and secure user management without server-side session storage.
vs alternatives: More scalable than traditional session management, as it does not require server-side session storage.
This capability provides advanced data visualization features using libraries like D3.js and Chart.js to create interactive charts and graphs. It supports various chart types and allows users to customize visual elements dynamically. The integration with the dashboard enables real-time updates of visualizations as new data comes in, enhancing user engagement and understanding.
Unique: Combines D3.js and Chart.js for a versatile charting solution that supports both static and dynamic data visualizations.
vs alternatives: More interactive than static charting libraries, providing real-time updates and user interactions.
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 kiwoom-hts-dashboard at 22/100. kiwoom-hts-dashboard leads on ecosystem, while Supabase is stronger on quality.
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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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