| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes CoinAPI's REST endpoints through the Model Context Protocol (MCP), allowing Claude and other MCP-compatible clients to query live cryptocurrency prices, market data, and exchange rates without direct API calls. Implements MCP's resource and tool abstractions to translate HTTP requests into standardized protocol messages, handling authentication via API key injection and response serialization into structured JSON for LLM consumption.
Unique: Bridges CoinAPI's REST interface directly into MCP's standardized tool/resource model, enabling Claude to access financial data through the same protocol used for local file systems and web search — no custom client code needed. Uses MCP's native authentication handling to inject API keys server-side, preventing credential exposure to the LLM.
vs alternatives: Simpler than building custom Claude plugins or function-calling wrappers because MCP handles protocol negotiation and serialization automatically; more secure than passing raw API keys to the model because credentials stay server-side.
Queries CoinAPI's unified data layer to fetch prices across 500+ cryptocurrency assets and 100+ exchanges, automatically routing requests to the most reliable or lowest-latency exchange for a given pair. Implements exchange selection logic (fallback chains, latency weighting) and normalizes responses into a canonical price format regardless of source exchange, abstracting away exchange-specific quirks and data inconsistencies.
Unique: Implements exchange routing and fallback logic at the MCP server layer, not in the client — Claude sees a single unified price endpoint but the server handles complexity of selecting optimal exchange, retrying failed requests, and normalizing format. This keeps the LLM's context clean and enables server-side caching/optimization.
vs alternatives: More reliable than querying individual exchange APIs because CoinAPI handles exchange-specific authentication and data format translation; faster than client-side aggregation because routing decisions happen server-side with cached exchange metadata.
Translates between arbitrary cryptocurrency and fiat currency pairs (e.g., BTC→EUR, ETH→JPY) by querying CoinAPI's conversion endpoints, which internally resolve multi-hop paths through major trading pairs. Handles edge cases like stablecoins, wrapped tokens, and illiquid pairs by falling back to secondary pricing sources or returning confidence scores. Exposes conversion rates with timestamp and source exchange metadata for transparency.
Unique: Abstracts away the complexity of multi-hop currency conversions (e.g., BTC→USDT→EUR) by resolving paths server-side and returning a single canonical rate. Includes confidence scoring and alternative rate suggestions when primary path is illiquid, enabling Claude to make informed decisions about conversion reliability.
vs alternatives: More transparent than black-box conversion APIs because it returns source exchange and confidence metadata; more reliable than direct exchange APIs because CoinAPI handles fallback routing when primary pairs are unavailable.
Exposes CoinAPI's exchange catalog and trading pair index through MCP, allowing clients to discover available exchanges, their supported trading pairs, trading hours, and fee structures. Implements filtering and search logic to find pairs matching criteria (e.g., 'all BTC pairs on Binance', 'all USD stablecoin pairs'). Returns structured metadata including pair symbols, minimum order sizes, and fee tiers for each exchange.
Unique: Caches exchange metadata server-side and implements client-side filtering logic, reducing API calls compared to fetching full catalogs repeatedly. Normalizes exchange-specific pair naming conventions into a canonical format, allowing Claude to query across exchanges with consistent syntax.
vs alternatives: More efficient than querying individual exchange APIs because CoinAPI maintains a unified index; more discoverable than manual documentation because it exposes metadata programmatically with filtering capabilities.
Implements the MCP server specification by registering CoinAPI operations as MCP tools (for function-calling) and resources (for context injection). Each tool maps to a CoinAPI endpoint with schema validation, parameter documentation, and error handling. Resources expose static data (exchange lists, supported assets) that Claude can reference without making API calls. Handles MCP's request/response serialization, authentication token injection, and capability negotiation with the client.
Unique: Implements full MCP server lifecycle (initialization, capability negotiation, request handling, error propagation) for CoinAPI, not just a thin wrapper. Includes schema validation and documentation generation for tools, enabling Claude to understand parameter requirements without external documentation.
vs alternatives: More robust than custom function-calling wrappers because MCP handles protocol versioning and client compatibility; more maintainable than direct API integration because MCP abstracts away HTTP details and provides standardized error handling.
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 coinapi-mcp-server at 22/100. coinapi-mcp-server leads on ecosystem, while Supabase is stronger on quality.
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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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