| 0 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability allows users to initiate cloud builds for Expo and React Native projects through a simple command interface. It leverages a RESTful API to communicate with cloud services, ensuring that builds are queued and executed with real-time status updates. The implementation utilizes a job scheduling pattern to manage build requests efficiently, providing logs for each build process to facilitate debugging.
Unique: Integrates directly with Expo's cloud services for seamless build management, unlike other tools that require manual configuration.
vs alternatives: More integrated with Expo's ecosystem than standalone CI/CD tools, reducing setup time.
This capability enables users to publish over-the-air updates to their Expo applications directly from the command line. It uses a combination of the Expo API and a local file watcher to detect changes in the project, automatically packaging and deploying updates without requiring a full app store submission. The implementation follows a publish-subscribe model to notify users of the update status.
Unique: Utilizes Expo's built-in OTA update capabilities, which are optimized for quick deployments compared to traditional methods.
vs alternatives: Faster than manual app store submissions, allowing for immediate user access to updates.
This capability automates the submission process of applications to both the App Store and Google Play. It integrates with the respective APIs to handle the submission workflow, including metadata management and status tracking. The architecture employs a state machine pattern to manage the various stages of submission, ensuring that users are informed of any issues that arise during the process.
Unique: Automates the entire submission process using API integrations, reducing manual errors and improving efficiency.
vs alternatives: More streamlined than manual submissions via web interfaces, minimizing potential for human error.
This capability runs diagnostics on Expo and React Native projects to validate configurations and identify issues. It employs a modular architecture that allows for the execution of various diagnostic checks, leveraging predefined rules and heuristics to assess project health. The results are presented in a structured format, making it easy for developers to understand and resolve issues.
Unique: Utilizes a modular diagnostic engine that can be extended with custom checks, unlike static analysis tools.
vs alternatives: More flexible and customizable than standard linting tools, allowing for tailored diagnostics.
This capability provides users with quick access to relevant documentation based on the context of their project. It uses a context-aware search algorithm that analyzes project files and user queries to retrieve the most pertinent documentation. The implementation employs a lightweight indexing system that allows for fast retrieval of documentation without heavy resource usage.
Unique: Employs a context-aware search mechanism that tailors results based on project context, unlike static documentation tools.
vs alternatives: Faster and more relevant than traditional documentation searches, which can be cumbersome.
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 Expo Dev Assistant at 29/100.
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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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