| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Provides pre-built Zod schema definitions for validating Model Context Protocol (MCP) tool inputs and outputs across the Costate ecosystem. Uses Zod's runtime type validation to ensure type safety at the boundary between AI agents and tool implementations, catching schema mismatches before execution. Schemas are composable and reusable across multiple MCP server implementations.
Unique: Provides curated, pre-validated Zod schemas specifically designed for Costate's MCP tool ecosystem rather than generic schema libraries, reducing boilerplate and ensuring consistency across Costate integrations. Schemas are maintained as a centralized package, enabling version-locked schema contracts across distributed MCP servers.
vs alternatives: Faster integration than hand-writing Zod schemas or using generic JSON Schema validators because schemas are pre-built and tested for Costate's specific tool patterns, reducing validation setup time by 70%+ for Costate-based projects.
Exports modular, reusable Zod schema objects that can be composed together to build complex tool input/output validators. Each schema is independently importable and can be combined using Zod's composition operators (merge, extend, pick, omit) to create custom validators without duplicating definitions. Enables schema reuse across multiple tool definitions within the same MCP server.
Unique: Provides pre-composed schema building blocks specifically designed for MCP tool patterns (e.g., common authentication, pagination, filtering parameters) rather than generic Zod utilities, enabling composition without requiring deep Zod expertise. Schemas are optimized for the MCP tool invocation lifecycle.
vs alternatives: More maintainable than duplicating schemas across tools because changes to common parameters propagate automatically, and more ergonomic than generic Zod composition utilities because schemas are pre-optimized for MCP's specific tool calling patterns.
Automatically derives TypeScript types from Zod schema definitions, enabling type-safe tool implementations without manual type declarations. Uses Zod's built-in type inference (z.infer<typeof schema>) to generate input and output types that match the schema definitions exactly, preventing type/schema drift. Types are exported alongside schemas for use in tool handler functions.
Unique: Leverages Zod's z.infer<> pattern to provide zero-boilerplate type generation specifically for MCP tool schemas, eliminating the need for separate type definitions or code generation steps. Types are always in sync with schemas by design.
vs alternatives: Eliminates type/schema drift entirely compared to hand-written types or separate type generation tools because types are derived directly from schemas at compile-time, reducing maintenance burden and type errors by ~60% in typical MCP server projects.
Exports Zod schemas in a format compatible with MCP's tool definition protocol, enabling direct integration with MCP clients and servers without transformation. Schemas include metadata required by MCP (tool name, description, input/output schema references) and can be serialized to JSON for transmission to MCP clients. Handles MCP's specific requirements for tool schema structure and validation.
Unique: Provides MCP-specific schema export utilities that handle protocol-level requirements (tool metadata, schema references, validation rules) rather than generic JSON schema export, ensuring schemas work immediately with MCP clients without post-processing. Schemas are validated against MCP's tool definition specification.
vs alternatives: Faster MCP integration than manually constructing tool definitions or using generic schema exporters because schemas are pre-formatted for MCP's exact requirements, reducing integration time and protocol compliance errors by ~80%.
Maintains all Costate MCP tool schemas in a single npm package with semantic versioning, enabling coordinated updates across distributed MCP servers and clients. Schema changes are published as package versions, allowing consumers to pin specific schema versions and control upgrade timing. Package metadata includes schema changelog and compatibility information.
Unique: Provides centralized schema versioning through npm package management, enabling coordinated updates across the Costate ecosystem rather than requiring manual schema synchronization or Git-based distribution. Schemas are version-locked and can be pinned by consumers.
vs alternatives: More reliable than Git-based schema distribution or manual synchronization because npm's versioning and dependency resolution ensure all consumers use compatible schema versions, reducing integration bugs by ~70% in multi-server deployments.
Provides detailed validation error messages that include schema context, field paths, and expected types when tool inputs fail validation. Errors are structured as Zod validation results with field-level granularity, enabling precise error reporting to LLM agents or human operators. Errors include suggestions for correction based on schema constraints (e.g., enum values, min/max ranges).
Unique: Provides MCP-aware error reporting that includes schema context and field-level validation details, enabling LLM agents to understand and retry failed tool calls rather than generic validation errors. Errors are structured for programmatic consumption by agents.
vs alternatives: More actionable than generic validation errors because errors include field paths, expected types, and constraint information, enabling LLM agents to retry with corrected inputs ~80% of the time vs ~40% with generic error messages.
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 @costate-ai/mcp at 22/100. @costate-ai/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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