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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes Australian Pharmaceutical Benefits Scheme (PBS) medicine database through Model Context Protocol (MCP) server interface, enabling Claude and other MCP-compatible clients to query medicine information, pricing, and availability without direct API calls. Implements FastAPI backend that translates MCP tool calls into structured PBS data lookups, abstracting authentication and data transformation complexity from the client.
Unique: Bridges Claude's native MCP protocol with Australian PBS data through FastAPI, eliminating need for clients to manage PBS authentication or implement custom data transformation logic. Positions PBS as a first-class tool in Claude conversations rather than requiring external API orchestration.
vs alternatives: Simpler integration than building custom REST API wrappers — MCP protocol handles tool discovery and schema negotiation automatically, reducing boilerplate compared to manual API client implementations.
Provides structured query interface for searching PBS medicine database by multiple criteria including medicine name, PBS item code, therapeutic classification, and listing status. Implements server-side filtering and ranking logic to return relevant results with complete metadata (pricing, subsidy information, restrictions) in standardized JSON format, enabling precise medicine lookups without client-side post-processing.
Unique: Implements server-side filtering against PBS database rather than returning raw data for client-side filtering, reducing bandwidth and enabling server-optimized query patterns. Exposes PBS-native filtering dimensions (therapeutic classification, listing status) directly as query parameters.
vs alternatives: More efficient than client-side filtering of large medicine datasets because filtering happens at the data source, and results include pre-computed pricing and subsidy information rather than requiring separate enrichment calls.
Extracts and structures pricing, subsidy, and patient cost information from PBS records for queried medicines. Parses PBS data to separate government subsidy amounts, patient co-payment requirements, and any safety net thresholds, returning this financial data in standardized format suitable for cost analysis, patient education, or healthcare system modeling. Handles complex PBS pricing rules including tiered subsidies and special patient categories.
Unique: Parses PBS pricing rules into structured financial components (subsidy amount, patient cost, safety net threshold) rather than returning raw PBS text, enabling programmatic cost calculations and comparisons. Handles PBS-specific pricing complexity including tiered subsidies and special patient categories.
vs alternatives: More actionable than raw PBS pricing text because it separates government subsidy from patient cost, enabling direct cost comparisons and budget modeling without manual parsing of PBS pricing rules.
Queries PBS database to determine current listing status of medicines (currently listed, restricted, delisted, or pending) and provides availability information including effective dates and any restrictions on prescribing or dispensing. Implements status classification logic that maps PBS listing codes to human-readable availability states, enabling applications to filter medicines by current availability and alert users to status changes.
Unique: Translates PBS listing codes into structured availability states with restriction details, enabling applications to make availability-aware medicine recommendations without requiring users to interpret raw PBS status codes. Integrates status information with pricing and medicine metadata for holistic availability assessment.
vs alternatives: More actionable than raw PBS status codes because it provides human-readable availability states and restriction summaries, enabling clinical decision support without requiring users to reference separate PBS documentation.
Automatically generates and exposes MCP-compliant tool schemas for all PBS query capabilities, enabling Claude and other MCP clients to discover available tools, understand required parameters, and validate inputs before making requests. Implements FastAPI route handlers that conform to MCP tool specification, including parameter descriptions, type definitions, and example values, allowing clients to build dynamic UIs or validate queries programmatically.
Unique: Leverages FastAPI's automatic OpenAPI schema generation to produce MCP-compliant tool definitions, eliminating manual schema maintenance and ensuring tool schemas always match implementation. Exposes PBS query capabilities as first-class MCP tools rather than requiring custom client-side tool definitions.
vs alternatives: Simpler than manually maintaining separate tool schema definitions because FastAPI automatically generates schemas from route definitions, reducing schema drift and enabling rapid iteration on PBS query capabilities.
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 PBS API at 23/100.
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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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