| 0 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Searches for movies and TV shows across multiple data sources (IMDb, TMDB, local databases, or custom crawlers) and aggregates results into a unified response format. The MCP server implements a source-agnostic query interface that routes search requests to configured providers, normalizes heterogeneous result schemas, and returns deduplicated matches ranked by relevance and data completeness.
Unique: Implements MCP tool protocol for seamless LLM integration with pluggable source adapters, allowing Claude and other MCP-compatible clients to search movies without custom API wrappers or context management
vs alternatives: Provides MCP-native movie search vs. generic REST API wrappers, enabling direct LLM tool calling without intermediate orchestration layers
Validates that found movie/TV show resources exist and are accessible across configured sources by performing existence checks, verifying data consistency between sources, and flagging incomplete or conflicting metadata. The validator cross-references results against multiple providers to ensure the resource is real and returns confidence scores based on source agreement and data completeness.
Unique: Implements cross-source validation logic within MCP tool protocol, allowing LLMs to automatically verify search results without external validation services or post-processing steps
vs alternatives: Validates movie data at search time vs. post-hoc validation, reducing downstream errors in recommendation or curation pipelines
Provides a plugin architecture for adding new movie/TV data sources without modifying core search logic. Each source adapter implements a standard interface (query, parse, normalize) that translates source-specific APIs (IMDb scraping, TMDB REST, local database queries) into the unified result schema. Adapters are registered at server startup and dynamically selected based on availability or configuration.
Unique: Uses adapter pattern to decouple source-specific logic from search orchestration, enabling runtime source swapping and custom backend integration without core library changes
vs alternatives: Extensible adapter system vs. hardcoded source support, allowing teams to integrate proprietary or custom movie databases without maintaining a fork
Transforms raw responses from different movie/TV sources (IMDb HTML, TMDB JSON, custom databases) into a unified, canonical schema with consistent field names, types, and formats. The mapping layer handles optional fields, type coercion, and null-safety, ensuring downstream consumers always receive predictable data structures regardless of source.
Unique: Implements schema mapping at the MCP tool boundary, ensuring LLMs always receive consistent data structures without needing to handle source-specific quirks
vs alternatives: Normalizes data at search time vs. requiring clients to handle source-specific schemas, reducing downstream complexity in LLM prompts and agent logic
Exposes movie search and validation capabilities as MCP tools that LLM clients (Claude, other MCP-compatible agents) can invoke directly through the Model Context Protocol. The server implements MCP tool definitions with JSON schemas for input validation, handles tool invocation requests, and returns results in MCP-compliant format, enabling seamless integration into LLM agent workflows without custom API clients.
Unique: Implements full MCP server lifecycle (tool definition, invocation handling, result serialization) for movie search, enabling drop-in integration with Claude and other MCP clients without custom wrappers
vs alternatives: Native MCP tool vs. REST API wrapper, eliminating the need for LLM agents to manage HTTP clients or parse API responses
Augments movie/TV search results with streaming availability data (which platforms host the content, subscription requirements, rental/purchase options) and video metadata (runtime, quality, subtitles). The enrichment layer queries streaming availability APIs or local databases and merges results into the canonical schema, providing users with actionable information about where to watch.
Unique: Integrates streaming availability as a first-class enrichment step in the search pipeline, allowing LLMs to make watch-location recommendations without separate API calls
vs alternatives: Includes streaming data in search results vs. requiring separate availability lookups, reducing latency and complexity for recommendation agents
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 @acwink/movies-search-mcp at 23/100. @acwink/movies-search-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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