| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 7 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes UI5 project structure, component hierarchies, and manifest metadata through MCP protocol endpoints. Parses manifest.json files, analyzes component dependencies, and extracts control definitions to provide LLM-accessible project context without requiring direct filesystem access. Uses MCP resource and tool abstractions to surface UI5-specific metadata as structured data.
Unique: Implements UI5-specific manifest parsing and component introspection as MCP tools, enabling LLMs to query live project context without custom API wrappers. Uses MCP's resource protocol to expose project metadata as queryable endpoints rather than static documentation.
vs alternatives: Provides direct LLM access to UI5 project structure via MCP protocol, eliminating need for custom REST APIs or manual context injection compared to generic code analysis tools.
Generates SAPUI5/OpenUI5 component code, controllers, and views with awareness of project manifest, available libraries, and component dependencies. Leverages extracted project metadata to suggest appropriate controls, namespaces, and library imports. Integrates with LLM code generation to produce UI5-compliant XML views, JavaScript controllers, and component definitions that match project conventions.
Unique: Integrates project manifest metadata into code generation context, enabling the LLM to generate UI5 code that respects library versions, namespace conventions, and available controls. Uses MCP tool responses to inject project-specific constraints into generation prompts.
vs alternatives: Generates UI5 code aware of project-specific library versions and conventions, unlike generic code generators that produce boilerplate without project context awareness.
Exposes UI5 development operations (component creation, manifest updates, control queries) as MCP tools with schema-based function calling. Implements MCP tool protocol to allow LLM clients to invoke UI5-specific functions with structured arguments and receive JSON responses. Handles tool invocation routing, argument validation, and error handling within the MCP server lifecycle.
Unique: Implements MCP tool protocol for UI5-specific operations, allowing LLMs to invoke UI5 development tasks via schema-validated function calls. Uses MCP's standardized tool calling mechanism rather than custom API endpoints.
vs alternatives: Provides standardized MCP tool calling for UI5 operations, enabling seamless integration with any MCP-compatible LLM client without custom API wrappers or protocol translation.
Parses and validates SAPUI5/OpenUI5 manifest.json files to extract application metadata, library dependencies, component definitions, and configuration. Implements manifest schema validation to ensure compliance with UI5 manifest specifications. Exposes parsed manifest data through MCP endpoints for LLM access, enabling context-aware code generation and project analysis.
Unique: Implements UI5 manifest schema validation and parsing as an MCP tool, allowing LLMs to query and validate application configuration without direct filesystem access. Exposes manifest metadata as structured data for context injection into code generation.
vs alternatives: Provides LLM-accessible manifest parsing and validation, enabling AI-assisted configuration analysis and generation compared to manual manifest inspection or generic JSON parsing tools.
Discovers available UI5 libraries, controls, and their properties by parsing library metadata and control definitions. Provides LLM-accessible queries to list available controls, retrieve control properties/aggregations, and identify compatible libraries for a given UI5 version. Implements caching of library metadata to optimize repeated queries and reduce filesystem I/O.
Unique: Implements control and library discovery as cached MCP queries, enabling LLMs to explore available UI5 controls and their properties without manual documentation lookup. Uses metadata caching to optimize repeated queries across multiple code generation requests.
vs alternatives: Provides LLM-accessible control discovery with property introspection, eliminating need for manual API documentation lookup compared to generic code completion tools without UI5 library awareness.
Implements MCP server initialization, resource registration, and lifecycle management for UI5 development context. Exposes UI5 project resources (components, views, controllers, manifests) through MCP resource protocol, allowing LLM clients to read and reference project files. Handles server startup, configuration loading, and graceful shutdown with proper resource cleanup.
Unique: Implements full MCP server lifecycle for UI5 projects, exposing project resources and tools through standardized MCP protocol. Handles server initialization, resource registration, and graceful shutdown as part of the MCP server implementation.
vs alternatives: Provides complete MCP server implementation for UI5 projects, eliminating need to build custom MCP servers or API wrappers compared to generic MCP frameworks without UI5-specific resource handling.
Provides context-aware code suggestions and completions for UI5-specific patterns (data binding syntax, control hierarchies, event handler patterns) by analyzing project context and manifest metadata. Integrates with LLM code generation to suggest appropriate UI5 idioms, control usage patterns, and best practices based on project configuration and available libraries.
Unique: Injects UI5 project context and manifest metadata into LLM code generation prompts to enable pattern-aware suggestions. Uses MCP tool responses to provide project-specific context for code completion without requiring custom IDE plugins.
vs alternatives: Provides context-aware UI5 code suggestions based on project manifest and configuration, unlike generic code completion tools that lack UI5-specific pattern awareness.
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 @ui5/mcp-server at 34/100. @ui5/mcp-server leads on adoption and 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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