| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 9 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Searches pharmaceutical databases across 8 CIS countries (Kazakhstan, Belarus, Kyrgyzstan, Russia, Ukraine, Georgia, Armenia, Azerbaijan) using a unified query interface that normalizes medicine names and returns aggregated pricing data from multiple pharmacy networks. Implements country-specific API adapters that handle regional pharmaceutical naming conventions, regulatory differences, and currency variations, then consolidates results into a standardized schema for comparison.
Unique: Unified MCP interface abstracting 8 distinct regional pharmacy APIs with country-specific normalization logic, handling Cyrillic naming conventions and regional regulatory differences that generic price-comparison tools don't address
vs alternatives: Covers underserved CIS markets with native regional API integrations, whereas global pharmacy APIs (GoodRx, Pharmacy.com) focus on US/EU and lack depth in post-Soviet countries
Locates pharmacies within a specified geographic radius or administrative boundary using country-specific pharmacy registries and geospatial indexing. Implements distance-based filtering that accounts for regional variations in pharmacy density and returns ranked results by proximity, availability of requested medicines, and user ratings where available.
Unique: Integrates country-specific pharmacy registries with geospatial indexing that handles regional coordinate system variations and pharmacy density differences across CIS markets, rather than relying on generic mapping APIs
vs alternatives: Native support for CIS pharmacy registries and regional coordinate systems provides better accuracy than Google Maps or OpenStreetMap-based solutions in underserved regions
Tracks historical price data for medicines across regions and time periods, enabling trend analysis, price volatility detection, and comparative pricing insights. Stores time-series price data indexed by medicine, pharmacy, region, and date, supporting queries for price changes, seasonal patterns, and cross-regional price differentials.
Unique: Maintains regional price history indexed by medicine, pharmacy, and date with support for multi-currency normalization and regional price volatility patterns specific to CIS pharmaceutical markets
vs alternatives: Provides CIS-specific price history that global pharmacy APIs don't track; enables regional trend analysis that generic time-series databases can't contextualize for pharmaceutical markets
Retrieves standardized pharmaceutical information including active ingredients, dosages, forms, regulatory status, and country-specific approval data from regional pharmaceutical registries. Normalizes medicine data across countries where the same drug may have different brand names, dosages, or regulatory classifications, and provides regulatory approval status for each region.
Unique: Aggregates regulatory metadata from 8 regional pharmaceutical registries with cross-country medicine equivalence mapping, handling Cyrillic naming conventions and regional regulatory classification differences
vs alternatives: Provides region-specific regulatory status and approval data that generic medicine databases (DrugBank, PubChem) don't include for CIS markets; enables compliance checking across multiple jurisdictions
Filters search results by pharmacy network, chain affiliation, or independent status, enabling queries like 'show only results from Pharmacy Chain X' or 'find independent pharmacies in this region'. Maintains a registry of pharmacy chains and networks across CIS countries with metadata about chain policies, delivery capabilities, and loyalty programs.
Unique: Maintains CIS-specific pharmacy chain registry with network affiliation metadata and chain-specific policies, enabling filtering and comparison that generic pharmacy APIs don't support
vs alternatives: Provides chain-aware filtering for CIS pharmacy networks, whereas global pharmacy APIs treat all pharmacies as independent entities without network context
Resolves medicine names across multiple languages and writing systems (Cyrillic, Latin, transliteration variants) used in CIS countries, normalizing user input to canonical medicine identifiers. Uses fuzzy matching and phonetic algorithms to handle misspellings, transliteration variations, and regional naming differences, then maps to standardized medicine IDs for consistent search results.
Unique: Implements Cyrillic-Latin transliteration normalization with fuzzy matching specifically for CIS pharmaceutical nomenclature, handling regional spelling variations and transliteration inconsistencies
vs alternatives: Provides CIS-specific language handling that generic medicine search APIs don't support; enables seamless search across Cyrillic and Latin input without user language selection
Aggregates real-time or near-real-time stock availability data from pharmacy networks, indicating whether a medicine is in stock, out of stock, or available for pre-order. Implements polling or webhook-based updates from pharmacy inventory systems and normalizes availability status across different pharmacy reporting formats and update frequencies.
Unique: Aggregates inventory data from multiple CIS pharmacy networks with varying update frequencies and formats, normalizing to a unified availability schema with timestamp tracking for data freshness
vs alternatives: Provides real-time inventory aggregation across CIS pharmacy networks, whereas global pharmacy APIs typically show only pricing without current stock status
Identifies and filters pharmacies by delivery and fulfillment capabilities (in-store pickup, home delivery, mail delivery, same-day delivery) with estimated delivery times and associated costs. Queries pharmacy metadata for supported fulfillment methods and integrates with delivery logistics data to provide realistic delivery time estimates.
Unique: Aggregates delivery capability metadata from CIS pharmacy networks with region-specific delivery time estimates, accounting for geographic and infrastructure differences across countries
vs alternatives: Provides CIS-specific delivery options and realistic time estimates for underserved regions, whereas global pharmacy APIs focus on urban delivery in developed markets
+1 more 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.
apteka-cis scores higher at 42/100 vs Supabase at 42/100.
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