| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability allows users to transform and format text using a variety of built-in functions. It employs a modular architecture that enables quick access to different transformation methods, such as trimming whitespace, changing case, or applying custom formatting rules. The toolkit is designed to be extensible, allowing developers to add their own formatting functions easily, which enhances its versatility compared to static libraries.
Unique: Utilizes a modular approach to allow for easy integration of custom formatting functions, making it highly adaptable.
vs alternatives: More flexible than standard libraries due to its extensibility for custom transformations.
This capability provides functions to encode, decode, and escape strings for safe transmission across different platforms. It uses established encoding standards (like Base64 and URL encoding) and implements a consistent API for developers to easily integrate into their applications. The toolkit ensures that all encoded strings maintain their integrity when shared across various web applications.
Unique: Focuses on providing a consistent API for various encoding methods, making it easier for developers to implement secure data handling.
vs alternatives: Simpler and more unified than using multiple libraries for different encoding needs.
This capability analyzes the readability of text using established metrics such as Flesch-Kincaid and Gunning Fog indices. It processes input text to calculate scores and provides feedback on sentence structure and word choice. The implementation uses natural language processing techniques to assess the complexity of the text, making it a valuable tool for content creators aiming to improve clarity.
Unique: Incorporates multiple readability metrics into a single analysis function, providing comprehensive insights.
vs alternatives: Offers a broader range of metrics than most standalone readability tools.
This capability generates universally unique identifiers (UUIDs) and various hash values (like SHA-256) on demand. It utilizes cryptographic libraries to ensure that the generated hashes are secure and collision-resistant. The toolkit provides a simple API for developers to request unique identifiers or hashed values, making it easy to integrate into applications that require unique keys or secure data storage.
Unique: Combines UUID and hash generation in a single toolkit, providing a streamlined approach for developers.
vs alternatives: More integrated than using separate libraries for UUID and hash generation.
This capability allows users to perform complex regex operations such as searching, replacing, and validating strings against regular expressions. It leverages a robust regex engine that supports advanced features like lookaheads and backreferences, enabling developers to handle intricate text processing tasks. The toolkit also provides a user-friendly interface for constructing and testing regex patterns, which simplifies the development process.
Unique: Offers a comprehensive regex testing interface alongside execution capabilities, enhancing usability for developers.
vs alternatives: More user-friendly than traditional regex libraries due to its integrated testing features.
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 text-toolkit at 28/100.
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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