| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability allows users to register and verify decentralized identities using a blockchain-based approach. It employs smart contracts to ensure that identity claims are immutable and verifiable, enabling secure interactions within a decentralized network. The architecture leverages on-chain registries to facilitate real-time verification, ensuring that identity checks are both efficient and trustworthy.
Unique: Utilizes a unique combination of smart contracts and on-chain registries to provide real-time identity verification, enhancing trust in decentralized interactions.
vs alternatives: More efficient than traditional identity verification systems due to its on-chain architecture, reducing the need for third-party intermediaries.
This capability tracks and manages reputation scores for users within the decentralized network. It employs a scoring algorithm that aggregates user interactions and feedback, updating scores in real-time via smart contracts. The system is designed to be transparent and tamper-proof, ensuring that reputation scores reflect genuine user behavior and interactions.
Unique: Incorporates real-time updates and transparency through blockchain technology, ensuring that reputation scores are both accurate and trustworthy.
vs alternatives: Offers a more reliable and transparent reputation management system compared to centralized solutions, reducing the risk of manipulation.
This capability enables the issuance of verifiable credentials to users, allowing them to prove their identity or qualifications securely. It uses a decentralized framework where credentials are stored on the blockchain, ensuring they are tamper-proof and easily verifiable by third parties. The system supports various credential types and integrates seamlessly with existing identity management solutions.
Unique: Utilizes blockchain technology to ensure that issued credentials are secure and verifiable, providing a higher level of trust compared to traditional methods.
vs alternatives: More secure and reliable than traditional credentialing systems, as it eliminates the risk of forgery and provides instant verification.
This capability allows users to track their credit balances on-chain, providing real-time visibility into available credits for transactions. It leverages smart contracts to manage credit issuance and redemption, ensuring that all transactions are recorded immutably on the blockchain. Users can query their balances and transaction history through a user-friendly interface.
Unique: Integrates real-time credit tracking with blockchain technology, ensuring that all transactions are transparent and verifiable.
vs alternatives: Offers more transparency and reliability than traditional credit tracking systems, which can be prone to errors and fraud.
This capability allows users to execute queries against on-chain registries to retrieve necessary information for transactions or identity verification. It employs a structured query language tailored for blockchain data, enabling efficient retrieval of relevant records. The system is designed to handle complex queries while ensuring data integrity and security.
Unique: Utilizes a specialized query language for efficient on-chain data retrieval, ensuring that queries are both secure and performant.
vs alternatives: More efficient than traditional database queries for blockchain data, as it is designed specifically for the unique structure of on-chain records.
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 MolTrust at 41/100.
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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
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