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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 12 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Enables programmatic video file uploads to Mux's distributed infrastructure with support for direct file uploads, URL-based ingestion, and multipart streaming. The SDK abstracts the underlying HTTP client layer (APIClient.post/put methods) to handle authentication via token ID/secret pairs, automatic retry logic, and response parsing into typed Asset objects. Supports both synchronous uploads and asynchronous processing workflows where video transcoding happens server-side after ingestion.
Unique: Provides typed SDK abstractions over Mux's multipart upload and direct URL ingestion APIs with built-in HMAC authentication and automatic HTTP client configuration, eliminating manual HTTP header construction and credential management that would be required with raw fetch/axios calls.
vs alternatives: Simpler than raw API calls (no manual auth headers or multipart encoding) and more feature-complete than generic upload libraries because it understands Mux-specific metadata fields and playback ID generation.
Provides programmatic creation and management of live streaming sessions through Mux's Live API, exposing CRUD operations for live stream objects that generate RTMP ingest URLs and playback IDs. The SDK wraps the underlying APIClient methods to handle authentication and response marshaling, enabling developers to create streams with custom settings (resolution, bitrate, latency profiles), retrieve stream status, and terminate sessions. Live streams are created as persistent resources that can be reused across multiple broadcast sessions.
Unique: Abstracts Mux's live stream lifecycle management into typed SDK methods that handle credential generation and RTMP URL construction, whereas competitors like Twitch API require manual stream key management and separate ingest endpoint discovery.
vs alternatives: More developer-friendly than raw REST API calls because it automatically constructs RTMP URLs and manages stream state transitions; simpler than building custom streaming infrastructure because Mux handles transcoding and CDN distribution.
Provides automatic pagination handling for list operations that return large result sets. The SDK's list methods accept pagination parameters (limit, offset or cursor) and return paginated responses with metadata (total_count, has_more). Developers can iterate through pages manually or use helper methods that abstract away pagination logic. The SDK handles cursor-based pagination transparently, allowing developers to fetch all results without manually constructing pagination queries.
Unique: Provides automatic pagination handling through SDK methods that abstract away cursor management and sequential page fetching, whereas raw API calls require developers to manually construct pagination queries and track cursor state across requests.
vs alternatives: More convenient than manual pagination because the SDK handles cursor tracking; more efficient than loading all results at once because pagination allows streaming large datasets.
Provides structured error handling with automatic retry logic for transient failures. The SDK wraps API responses and translates HTTP error codes into typed error objects (APIError, RateLimitError, AuthenticationError, etc.) with detailed error messages and metadata. Automatic retry logic handles transient failures (5xx errors, timeouts) with exponential backoff, whereas permanent failures (4xx errors) fail immediately. Developers can configure retry behavior (max attempts, backoff strategy) through client options.
Unique: Provides automatic retry logic with exponential backoff for transient failures, whereas raw HTTP clients require manual retry implementation. Typed error objects enable compile-time error handling and IDE autocomplete for error cases.
vs alternatives: More robust than manual retry logic because the SDK handles exponential backoff and transient failure detection; more maintainable than custom error handling because error types are standardized across all API operations.
Enables configuration of playback restrictions and digital rights management (DRM) for video assets through the SDK's playback policy APIs. Developers can set signed playback tokens (JWT-based), geo-blocking rules, IP whitelisting, and DRM provider integration (Widevine, FairPlay) at the asset or stream level. The SDK provides JWT signing utilities (using jwtSigningKey and jwtPrivateKey) to generate time-limited, cryptographically signed playback tokens that restrict access to specific playback IDs.
Unique: Provides built-in JWT signing utilities that generate cryptographically signed playback tokens with Mux-specific claims (playback ID, expiration), eliminating the need for developers to implement custom JWT signing logic or manage separate token services.
vs alternatives: More integrated than generic JWT libraries because it understands Mux's playback token schema and automatically includes required claims; more secure than URL-based access tokens because JWT signatures prevent tampering.
Provides programmatic access to Mux's Data API for querying video engagement metrics, viewer analytics, and performance data. The SDK exposes methods to retrieve video views, playback metrics (bitrate, resolution, buffering), and custom dimensions/filters for segmenting data by geography, device type, or custom metadata. Queries are constructed through a fluent API that builds filter expressions and dimension selections, which are then executed via the APIClient.get() method and returned as structured metric objects.
Unique: Provides typed SDK methods for constructing complex analytics queries with filter and dimension support, whereas raw API calls require manual query parameter construction and JSON serialization. Includes built-in pagination handling and response marshaling into typed metric objects.
vs alternatives: More discoverable than raw REST API because the SDK exposes available dimensions and filters through TypeScript interfaces; more efficient than building custom analytics pipelines because Mux pre-aggregates data server-side.
Provides cryptographic verification of incoming Mux webhook events using HMAC-SHA256 signature validation. The SDK exposes a webhook verification method that accepts the raw request body and signature header, validates the signature against the configured webhookSecret, and returns the parsed event payload if valid. This prevents processing of forged or tampered webhook events. The SDK also provides TypeScript types for all Mux webhook event types (video.created, live_stream.started, etc.), enabling type-safe event handling in webhook handlers.
Unique: Provides a single SDK method for HMAC-SHA256 signature verification that handles the cryptographic validation internally, whereas developers using raw HTTP libraries must manually construct the signature and compare it to the header value. Includes TypeScript types for all Mux event types, enabling IDE autocomplete and compile-time type checking.
vs alternatives: More secure than manual signature verification because it uses constant-time comparison to prevent timing attacks; more convenient than generic webhook libraries because it understands Mux's specific event schema and signature format.
Exposes Mux API capabilities as dynamically generated MCP tools that can be called by AI assistants and LLM agents. The MCP server (@mux/mcp package) wraps the underlying Mux SDK and generates tool definitions (name, description, input schema) for each API operation, allowing Claude or other MCP-compatible clients to discover and invoke Mux operations conversationally. Tool schemas are generated from the SDK's TypeScript types, ensuring consistency between SDK and MCP interfaces. The server handles authentication, error translation, and response formatting automatically.
Unique: Automatically generates MCP tool definitions from the underlying Mux SDK's TypeScript types, ensuring that tool schemas stay in sync with API capabilities without manual tool definition maintenance. Handles authentication and error translation transparently, allowing AI assistants to invoke Mux operations without understanding API details.
vs alternatives: More maintainable than manually-defined MCP tools because schema generation is automated; more discoverable than raw API documentation because tools are self-describing through MCP's tool discovery protocol.
+4 more capabilities
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 Mux at 27/100.
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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
+1 more capabilities