| 0 |
| 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes CoinCap's public REST API endpoints through MCP protocol, enabling Claude and other MCP clients to query current cryptocurrency prices, market caps, and 24h volume data without authentication overhead. Implements HTTP client abstraction that translates MCP tool calls into CoinCap API requests, parsing JSON responses into structured data for LLM consumption.
Unique: Eliminates authentication friction by leveraging CoinCap's public API tier, allowing MCP clients to access crypto data without managing secrets or API keys — implemented as a thin HTTP proxy layer that translates MCP tool schemas directly to CoinCap REST endpoints
vs alternatives: Simpler deployment than building custom crypto data integrations or using authenticated APIs like CoinGecko Pro, since it requires zero credential management while still providing real-time market data
Implements MCP server protocol to expose cryptocurrency data retrieval as callable tools with structured JSON schemas, enabling Claude and other MCP clients to discover, invoke, and chain crypto data queries within conversations. Uses MCP's tool definition format to describe parameters (symbol, currency), return types, and descriptions that guide LLM tool selection and parameter binding.
Unique: Implements MCP server protocol natively rather than wrapping a generic HTTP client, allowing Claude and other MCP clients to discover and invoke crypto tools with full schema awareness — enables automatic tool selection and parameter binding without manual prompt engineering
vs alternatives: More discoverable and composable than REST API documentation or custom prompt instructions, since MCP schema definitions allow Claude to understand tool capabilities, parameters, and return types automatically
Supports querying multiple cryptocurrency prices in a single MCP tool invocation by accepting comma-separated or array-formatted symbol lists, then aggregating results from CoinCap API into a unified response. Implements client-side batching logic that may issue multiple HTTP requests to CoinCap but returns consolidated JSON to the MCP caller, reducing round-trip overhead for agents querying multiple assets.
Unique: Implements client-side batch aggregation that translates single MCP tool calls into multiple CoinCap API requests, then consolidates results — reduces MCP round-trips while respecting CoinCap's per-request rate limits
vs alternatives: More efficient than making separate MCP tool calls for each cryptocurrency, since it reduces Claude's tool invocation overhead and consolidates network requests into a single response
Accepts optional currency parameter (USD, EUR, GBP, etc.) in price queries and returns cryptocurrency prices converted to the specified fiat currency using CoinCap's built-in conversion rates. Implements parameter validation to ensure only supported currencies are requested, then appends currency code to API requests and formats output with localized currency symbols and decimal precision.
Unique: Delegates currency conversion to CoinCap's API rather than implementing client-side forex logic, ensuring consistency with CoinCap's official rates and reducing maintenance burden for currency pair management
vs alternatives: Simpler than integrating a separate forex API, since CoinCap provides built-in conversion rates for all supported currencies in a single API call
Implements error handling layer that catches CoinCap API failures (rate limits, timeouts, invalid symbols) and translates them into user-friendly MCP error responses with diagnostic information. Uses exponential backoff or request queuing for rate-limit scenarios, validates symbol formats before API calls, and returns structured error objects indicating failure reason (invalid symbol, network timeout, rate limit) to help Claude understand and recover from failures.
Unique: Implements MCP-aware error handling that translates CoinCap API failures into structured MCP error responses with diagnostic context, enabling Claude to understand and respond to failures programmatically rather than receiving raw HTTP errors
vs alternatives: More robust than naive API wrapping, since it provides Claude with actionable error information and recovery suggestions rather than opaque HTTP status codes
Implements MCP server using stdio transport protocol, allowing the server to run as a subprocess and communicate with MCP clients (Claude Desktop, custom hosts) via standard input/output streams. Uses JSON-RPC message format over stdio to handle tool discovery, invocation, and result streaming without requiring HTTP server setup or port binding, enabling seamless integration with Claude Desktop and other stdio-based MCP clients.
Unique: Uses stdio transport instead of HTTP, eliminating port binding and network configuration overhead — implemented as a lightweight subprocess that communicates via JSON-RPC over standard streams, ideal for local development and Claude Desktop integration
vs alternatives: Simpler to deploy than HTTP-based MCP servers, since it requires no port management, firewall configuration, or network setup — just subprocess spawning and stdio piping
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 CoinCap at 24/100.
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