| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 7 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Parses binary MIDI files into structured event objects (note-on, note-off, control change, tempo, time signature) by reading variable-length quantities and status bytes according to the MIDI 1.0 specification. Leverages Tone.js's MIDI parsing infrastructure to handle multiple tracks, timing divisions, and meta-events while preserving absolute and relative timing information for downstream manipulation.
Unique: Built on Tone.js's battle-tested MIDI parser rather than implementing from scratch, providing immediate compatibility with Tone.js synthesizers and effects while exposing parsed events via MCP protocol for LLM integration
vs alternatives: Tighter integration with Tone.js ecosystem than generic MIDI libraries, enabling direct synthesis of parsed events without intermediate format conversion
Extracts and filters MIDI events by track index, channel, event type (note-on/off, CC, program change), or time range using in-memory array operations on the parsed event structure. Allows selective manipulation of multi-track MIDI files by creating new track subsets without modifying the original file, preserving timing relationships and metadata.
Unique: Operates on Tone.js-compatible event structures, allowing filtered results to be directly synthesized or re-exported without format conversion
vs alternatives: Simpler API than low-level MIDI libraries for common filtering tasks, but less performant than native C++ MIDI tools for large files
Constructs new MIDI events (note-on, note-off, control change, tempo, time signature) with specified parameters (pitch, velocity, duration, channel, timestamp) and inserts them into existing track structures at precise timing positions. Handles automatic delta-time recalculation when inserting events to maintain proper MIDI timing relationships and prevents timing conflicts through validation.
Unique: Integrates with Tone.js event model, allowing created events to be immediately synthesized or scheduled without intermediate serialization
vs alternatives: Higher-level API than raw MIDI byte manipulation, but less flexible than DAW scripting environments for complex musical transformations
Converts in-memory MIDI event structures back into binary MIDI file format (.mid) by encoding events as status bytes, variable-length quantities, and delta-time values according to MIDI 1.0 specification. Handles track chunking, header generation with timing division metadata, and file I/O to produce valid, playable MIDI files that can be opened in any DAW or MIDI player.
Unique: Produces Tone.js-compatible MIDI files that can be immediately loaded back into Tone.js for playback or further manipulation, creating a closed-loop workflow
vs alternatives: Simpler API than low-level MIDI encoding libraries, but less control over binary optimization than hand-crafted MIDI writers
Exposes MIDI parsing, filtering, creation, and export capabilities as MCP tools that can be called by LLM agents and other MCP clients through standardized request/response protocol. Handles tool schema definition, parameter validation, error handling, and result serialization to enable natural language composition of MIDI workflows (e.g., 'extract the melody from this MIDI file and transpose it up a fifth').
Unique: Bridges Tone.js MIDI capabilities with MCP protocol, enabling LLM agents to reason about and manipulate music through natural language without requiring music theory knowledge
vs alternatives: First-class MCP integration vs. generic MIDI libraries that require custom wrapper code; enables LLM-driven workflows that would be difficult to orchestrate with traditional APIs
Identifies and extracts tempo (BPM) and time signature meta-events from MIDI files, exposing them as structured data with absolute timestamps. Supports insertion of new tempo/time signature changes at arbitrary positions, enabling tempo mapping, time signature analysis, and rhythmic transformation of MIDI compositions while preserving musical structure.
Unique: Extracts tempo/time signature as first-class data structures rather than opaque meta-events, enabling programmatic analysis and modification of rhythmic properties
vs alternatives: More accessible than raw MIDI meta-event parsing, but less feature-rich than dedicated music analysis libraries for complex rhythmic analysis
Applies transformations to note pitch (transposition, octave shifting, scale quantization) and velocity (scaling, randomization, humanization) across MIDI events using mathematical operations on note data. Supports batch transformations across entire tracks or filtered subsets, enabling algorithmic music generation, humanization, and harmonic manipulation without manual event iteration.
Unique: Operates on Tone.js note objects, enabling direct synthesis of transformed notes without re-serialization
vs alternatives: Higher-level API than raw MIDI byte manipulation, but less musically sophisticated than DAW plugins with music theory awareness
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 midi-file-mcp at 24/100. midi-file-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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