| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Enables Claude and other MCP-compatible AI agents to deploy applications to 4EVERLAND hosting infrastructure by exposing deployment operations through the Model Context Protocol. Implements MCP server specification with tool definitions that map to 4EVERLAND's REST API endpoints, allowing agents to orchestrate deployments, manage projects, and configure hosting settings through standardized tool-calling interfaces without direct API knowledge.
Unique: Implements 4EVERLAND-specific MCP server that bridges AI agents directly to 4EVERLAND's hosting platform through standardized tool definitions, enabling Claude and other MCP clients to orchestrate deployments without custom integration code
vs alternatives: Provides native MCP integration for 4EVERLAND hosting, whereas generic deployment tools require custom API wrappers or lack AI-agent-first design
Defines and registers MCP-compliant tool schemas that expose 4EVERLAND hosting capabilities (project creation, deployment, configuration) as callable functions. Implements the MCP tools specification with JSON schema definitions for each operation, parameter validation, and response formatting, allowing MCP clients to discover available hosting operations and invoke them with type-safe parameters.
Unique: Implements MCP tool schema registration specifically for 4EVERLAND hosting operations, with schema-driven parameter validation and discovery, enabling AI clients to understand and invoke hosting functions without hardcoded knowledge
vs alternatives: More discoverable and type-safe than direct REST API calls, and more standardized than custom agent tool definitions
Translates MCP tool invocations into 4EVERLAND REST API calls, handling authentication, request formatting, error mapping, and response transformation. Acts as an adapter layer that converts MCP tool parameters into properly formatted HTTP requests to 4EVERLAND endpoints, manages API credentials securely, and maps API responses back to MCP-compatible output formats.
Unique: Implements request translation layer that maps MCP tool invocations to 4EVERLAND REST API calls with built-in authentication and response transformation, abstracting API complexity from MCP clients
vs alternatives: Cleaner than exposing raw 4EVERLAND API to agents, and more maintainable than embedding API logic in agent prompts
Exposes 4EVERLAND project and deployment lifecycle operations (create project, deploy, update configuration, check status, list deployments) as MCP tools. Enables agents to manage the full deployment workflow including project initialization, code deployment, environment configuration, and status monitoring, with each operation mapped to corresponding 4EVERLAND API endpoints.
Unique: Exposes 4EVERLAND's full project and deployment lifecycle as composable MCP tools, allowing agents to orchestrate multi-step deployment workflows without manual intervention
vs alternatives: More comprehensive than simple deployment triggers, and more agent-friendly than requiring manual API calls
Provides MCP tools for managing project environment variables and configuration settings on 4EVERLAND, allowing agents to set, update, and retrieve environment-specific configurations. Implements secure parameter handling for sensitive values (API keys, secrets) and maps configuration operations to 4EVERLAND's configuration management endpoints.
Unique: Provides MCP-native environment and configuration management for 4EVERLAND projects, enabling agents to handle sensitive configuration without exposing secrets in prompts or logs
vs alternatives: More secure than embedding secrets in deployment scripts, and more flexible than static configuration files
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 @4everland/hosting-mcp at 22/100. @4everland/hosting-mcp 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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