| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 8 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Provides a standardized MCP (Model Context Protocol) tool server implementation that abstracts away runner-specific details, allowing the same tool definitions to work across different MCP client implementations (Claude Desktop, custom runners, etc.) without modification. Uses a protocol-compliant server architecture that handles tool registration, request routing, and response serialization independent of the underlying transport or client framework.
Unique: Explicitly designed as runner-neutral, meaning it decouples tool implementation from the specific MCP client/runner being used, allowing the same server code to work with Claude Desktop, custom runners, or any MCP-compliant consumer without conditional logic or adapter patterns
vs alternatives: Avoids vendor lock-in to specific MCP runners by implementing pure protocol compliance, whereas many tool packages are tightly coupled to a single client implementation
Provides pre-built, validated tool definitions and schemas optimized for Cyrus integration, including parameter validation, type checking, and schema enforcement at the MCP server level. Implements schema validation that catches malformed tool invocations before they reach application code, reducing error handling boilerplate and ensuring type safety across the tool boundary.
Unique: Provides Cyrus-optimized tool schemas with built-in validation rather than generic MCP tool definitions, reducing the need for application-level parameter checking and ensuring consistency across Cyrus tool ecosystems
vs alternatives: Tighter integration with Cyrus than generic MCP tool libraries, with validation baked into the server rather than requiring manual checks in tool handlers
Enables bundling multiple independent tools into a single MCP server instance with automatic request routing, tool discovery, and lifecycle management. Implements a registry pattern where tools are registered with the server, and incoming MCP requests are routed to the appropriate handler based on tool name, with support for tool metadata exposure and dynamic tool registration.
Unique: Implements a registry-based composition model where multiple tools are registered into a single server with automatic routing and discovery, rather than requiring separate server instances per tool or manual request dispatching
vs alternatives: More efficient than running separate MCP servers per tool, and more maintainable than manual request routing in application code
Handles the low-level details of MCP protocol message serialization, deserialization, and transport-agnostic communication. Implements JSON-RPC style request/response handling with proper error formatting, message ID tracking, and protocol compliance, abstracting away transport concerns so tools can focus on business logic rather than protocol mechanics.
Unique: Abstracts MCP protocol serialization and transport handling into a reusable layer, allowing tool developers to write handlers as simple functions without worrying about JSON-RPC mechanics or message framing
vs alternatives: Reduces boilerplate compared to hand-rolling MCP protocol handling, and provides consistent error formatting across all tools in the server
Provides standardized error handling and response formatting for tool invocations, including automatic error serialization, stack trace handling, and MCP-compliant error responses. Catches exceptions from tool handlers and converts them into properly formatted MCP error responses with appropriate error codes and messages, preventing unhandled exceptions from crashing the server.
Unique: Implements centralized error handling at the MCP server level, catching all tool exceptions and converting them to protocol-compliant error responses, rather than requiring each tool to handle its own error serialization
vs alternatives: Prevents unhandled exceptions from crashing the server and ensures consistent error formatting across tools, versus requiring each tool handler to implement its own error handling
Automatically coerces and normalizes tool parameters from MCP requests into the expected types and formats, handling common type conversions (string to number, JSON string to object, etc.) and parameter name mapping. Reduces boilerplate in tool handlers by ensuring parameters arrive in the correct type without manual conversion logic.
Unique: Implements automatic parameter type coercion and normalization at the server level based on tool schemas, eliminating the need for each tool handler to manually convert parameter types
vs alternatives: Reduces boilerplate in tool handlers compared to manual type conversion, and provides consistent coercion behavior across all tools
Exposes tool metadata (name, description, parameters, return types) through the MCP protocol, enabling clients to discover available tools and their capabilities without hardcoding tool knowledge. Implements tool introspection that allows MCP clients to query tool schemas and documentation, supporting dynamic tool discovery and client-side UI generation.
Unique: Provides MCP-compliant tool discovery and introspection, allowing clients to query available tools and their schemas dynamically rather than relying on hardcoded tool knowledge
vs alternatives: Enables dynamic tool discovery versus static tool lists, and supports client-side UI generation from tool schemas
Handles asynchronous tool execution with proper promise management, timeout handling, and concurrent request processing. Allows tool handlers to be async functions that return promises, with automatic promise resolution and rejection handling at the MCP server level, supporting tools that perform I/O operations without blocking the server.
Unique: Implements native async/await support for tool handlers with automatic promise resolution and rejection handling, allowing tools to perform I/O without blocking the server or requiring callback-style code
vs alternatives: Cleaner than callback-based tool execution and more efficient than synchronous blocking, enabling high-concurrency tool servers
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 cyrus-mcp-tools at 21/100.
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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