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| Match Graph | 0 | 0 |
| Pricing | Paid | Free |
| Capabilities | 7 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Searches and discovers available MCP servers from a centralized registry or package index, allowing developers to browse compatible servers before installation. The tool likely maintains or queries a curated registry of MCP-compliant server implementations with metadata about capabilities, versions, and compatibility information.
Unique: unknown — insufficient data on whether mcp-get maintains its own registry, aggregates from multiple sources, or queries a community-maintained index
vs alternatives: Provides CLI-first discovery for MCP servers, reducing friction compared to manual GitHub searches or documentation browsing
Installs MCP servers from the registry into a local environment, handling dependency resolution, version pinning, and compatibility checks. The tool likely downloads server binaries or source code, resolves transitive dependencies, and configures the server for use with compatible MCP clients (Claude, IDEs, agents).
Unique: unknown — insufficient data on whether mcp-get uses npm/pip/cargo package managers as backends or implements custom installation logic specific to MCP server architecture
vs alternatives: Simplifies MCP server setup compared to manual installation from GitHub, reducing configuration errors and version mismatches
Manages installed MCP server versions, checks for updates, and handles upgrades or downgrades with compatibility validation. The tool tracks installed versions, compares against registry versions, and applies updates while preserving configuration and state where possible.
Unique: unknown — insufficient data on whether mcp-get implements semantic versioning constraints, compatibility matrices, or breaking-change detection
vs alternatives: Centralizes MCP server version tracking in one tool rather than managing each server's updates independently
Configures installed MCP servers with required settings, environment variables, and initialization parameters. The tool may generate configuration files, prompt for required credentials or API keys, and validate server readiness before exposing it to MCP clients.
Unique: unknown — insufficient data on whether mcp-get uses interactive prompts, configuration templates, or environment variable detection for server setup
vs alternatives: Streamlines MCP server configuration compared to manual editing of config files, reducing setup errors
Manages the runtime lifecycle of installed MCP servers, including starting, stopping, restarting, and monitoring status. The tool likely wraps process management (systemd, launchd, or custom process spawning) and provides unified control across multiple servers.
Unique: unknown — insufficient data on whether mcp-get uses native OS process managers, containerization, or custom process spawning
vs alternatives: Provides unified CLI control for MCP server lifecycle across multiple servers, reducing manual process management overhead
Lists all installed MCP servers, displays their versions, status, and metadata. The tool maintains a local inventory of installed servers and provides filtering or sorting capabilities to help developers understand their MCP environment.
Unique: unknown — insufficient data on whether mcp-get tracks server metadata in a local database, manifest file, or by scanning the filesystem
vs alternatives: Provides a single command to view all MCP servers instead of manually checking multiple installation directories
Uninstalls MCP servers and removes associated files, configuration, and dependencies. The tool handles cleanup of server artifacts, configuration files, and optionally removes unused transitive dependencies to free up disk space.
Unique: unknown — insufficient data on whether mcp-get tracks dependency graphs to safely remove only unused transitive dependencies
vs alternatives: Automates cleanup of MCP server artifacts compared to manual file deletion, reducing orphaned files and configuration
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 mcp-get at 23/100. mcp-get leads on quality, while Supabase is stronger on ecosystem. Supabase also has a free tier, making it more accessible.
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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
+1 more capabilities