| 0 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability allows users to perform authenticated queries on various blockchain data points, such as Bitcoin addresses and transactions. It utilizes a secure token-based authentication mechanism to ensure that only authorized users can access sensitive data. The integration with the Ordiscan API enables real-time data retrieval, leveraging efficient query handling and response formatting to deliver results in a structured manner.
Unique: Employs a token-based authentication system that integrates seamlessly with the Ordiscan API, allowing for secure and efficient data access.
vs alternatives: More secure and flexible than traditional REST APIs due to its token-based authentication model.
This capability provides access to a suite of 29 integrated tools for analyzing blockchain data. Each tool is designed to perform specific functions, such as querying transactions or analyzing collections, and they can be accessed through a unified API interface. This modular approach allows developers to easily combine tools for complex queries and analyses without needing to switch between different APIs.
Unique: Offers a comprehensive suite of 29 specialized tools under a single API, enabling streamlined access and integration for complex tasks.
vs alternatives: More versatile than single-function APIs, allowing for multi-faceted analysis without the need for multiple integrations.
This capability enables users to monitor blockchain events in real-time, such as new transactions or changes to Bitcoin addresses. It uses WebSocket connections to push updates to clients immediately as events occur, ensuring that users receive the most current data without polling the server. This architecture minimizes latency and improves the responsiveness of applications relying on real-time data.
Unique: Utilizes WebSocket technology for real-time event notifications, providing immediate updates without the overhead of continuous polling.
vs alternatives: Faster and more efficient than traditional polling methods, reducing latency and resource consumption.
This capability allows users to query information specifically related to BRC-20 tokens on the Bitcoin blockchain. It leverages specialized endpoints within the Ordiscan API to retrieve data such as token balances, transaction history, and metadata. The implementation ensures that queries are optimized for performance, allowing for quick access to token-related data.
Unique: Provides dedicated endpoints for BRC-20 token queries, ensuring optimized access to token-specific data on the Bitcoin blockchain.
vs alternatives: More specialized and efficient than general blockchain APIs, which may not support BRC-20 tokens directly.
This capability allows users to retrieve the complete transaction history for a specified Bitcoin address. It uses efficient indexing and caching strategies to ensure that historical data can be accessed quickly, even for addresses with a high volume of transactions. The API provides structured responses that include timestamps, amounts, and transaction IDs.
Unique: Utilizes advanced indexing and caching techniques to provide fast access to transaction histories, even for highly active addresses.
vs alternatives: Significantly faster than traditional blockchain explorers, which may not optimize for high-volume addresses.
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 Ordiscan MCP Server at 28/100.
Need something different?
Search the match graph →© 2026 Unfragile. Stronger through disorder.
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