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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 8 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Fetches and aggregates decentralized exchange pool data across 20+ blockchains (Ethereum, Polygon, Arbitrum, Optimism, Base, Solana, etc.) via the DexPaprika API, providing real-time pool metadata including liquidity, token pair composition, fee tiers, and protocol identifiers. The MCP server acts as a standardized interface layer that normalizes heterogeneous blockchain DEX schemas into a unified query model, enabling clients to request pools by blockchain, protocol, or token pair without managing chain-specific RPC endpoints or DEX contract ABIs.
Unique: Provides MCP-native abstraction over DexPaprika's unified DEX indexing layer, which aggregates 5M+ tokens and pools across 20+ blockchains with normalized schema — eliminates need for developers to manage chain-specific DEX contract interactions or maintain separate indexing infrastructure per blockchain
vs alternatives: Simpler than building custom multi-chain DEX aggregators using individual blockchain RPCs and DEX subgraphs; faster than querying The Graph separately for each chain due to pre-indexed, centralized data
Retrieves historical and real-time trading volume, price movements, and transaction counts for token pairs across DEX protocols. The capability aggregates volume metrics across multiple DEX venues on the same blockchain, providing traders with comprehensive liquidity and activity signals. Data is normalized into time-series format (hourly, daily aggregations) enabling trend analysis and volatility calculations without requiring manual data transformation or external analytics libraries.
Unique: Aggregates volume across multiple DEX protocols per blockchain in a single query, with normalized time-series output — avoids need to query individual DEX subgraphs or aggregate raw blockchain transaction data manually
vs alternatives: Faster than querying The Graph for multiple DEX subgraphs sequentially; more comprehensive than single-DEX APIs like Uniswap v3 subgraph which only cover one protocol
Resolves token identities across multiple blockchains, mapping token addresses to canonical symbols, decimals, logos, and chain-specific contract addresses. The capability handles wrapped/bridged token variants (e.g., USDC on Ethereum vs Polygon vs Arbitrum) and provides canonical token information to prevent address collisions and enable unified token tracking. Uses DexPaprika's centralized token registry which maintains mappings across 5M+ tokens, reducing need for manual address lookups or maintaining separate token lists per chain.
Unique: Maintains centralized canonical token registry across 5M+ tokens and 20+ blockchains, enabling single-query resolution vs maintaining separate token lists per chain or querying individual chain indexers
vs alternatives: More comprehensive than CoinGecko token API for multi-chain resolution; faster than querying individual blockchain explorers or DEX subgraphs for token metadata
Lists all supported DEX protocols and their availability across blockchains, enabling clients to discover which protocols operate on which chains and their relative market share. The capability returns protocol metadata including protocol type (AMM, order book, hybrid), supported token pairs, and total value locked (TVL) per protocol per chain. This enables dynamic protocol selection for routing and helps identify protocol-specific opportunities or constraints.
Unique: Provides unified protocol enumeration across 20+ blockchains in single query, with TVL and market share metrics — eliminates need to query individual DEX subgraphs or maintain manual protocol lists
vs alternatives: More efficient than querying The Graph for each DEX subgraph separately; provides cross-chain protocol comparison that individual DEX APIs cannot offer
Exposes DexPaprika DEX analytics capabilities through the Model Context Protocol (MCP) standard, enabling AI agents and LLM-based tools to invoke DEX queries via standardized function-calling schemas. The MCP server translates natural language requests from Claude or other MCP clients into structured API calls, handles authentication with DexPaprika API keys, manages rate limiting, and returns results in agent-friendly JSON format. This abstraction allows non-technical prompts like 'find high-volume USDC pairs on Ethereum' to be automatically converted to correct API parameters.
Unique: Implements MCP server pattern for DEX analytics, enabling LLM agents to invoke DexPaprika queries with automatic schema validation and error handling — eliminates need for agents to manage raw API calls or authentication
vs alternatives: More structured than raw API access for LLM agents; enables natural language queries vs requiring agents to construct API URLs manually
Provides metadata for all supported blockchains including chain IDs, RPC endpoints, block explorers, and native token information. The capability enables clients to dynamically discover supported chains and their properties without hardcoding chain lists. Returns standardized chain metadata (name, symbol, decimals, logo) enabling UI rendering and chain selection interfaces.
Unique: Provides unified blockchain metadata across 20+ chains in single query, enabling dynamic chain discovery without hardcoding chain lists or maintaining separate chain registries
vs alternatives: More comprehensive than individual chain APIs; enables dynamic chain support vs static chain lists in traditional multi-chain applications
Retrieves detailed composition of liquidity pools including token reserves, reserve ratios, and impermanent loss indicators. The capability tracks how much of each token is locked in pools and enables calculation of slippage for hypothetical trades. Provides real-time reserve data enabling traders to assess pool depth and identify thin liquidity conditions that may result in high slippage.
Unique: Aggregates reserve data across multiple DEX protocols with normalized schema, enabling slippage comparison across venues without querying individual DEX smart contracts or subgraphs
vs alternatives: Faster than querying individual DEX subgraphs for reserve data; more accurate than static liquidity estimates due to real-time reserve tracking
Provides historical price data (OHLCV: Open, High, Low, Close, Volume) for token pairs across DEX protocols at multiple time granularities (1m, 5m, 15m, 1h, 4h, 1d). Data is aggregated from on-chain transactions and normalized into candlestick format enabling technical analysis without requiring manual price calculation from transaction logs. Supports time range queries enabling backtesting and historical analysis.
Unique: Provides normalized OHLCV data across multiple DEX protocols and blockchains with standardized time intervals, eliminating need to aggregate raw transaction data or query individual DEX subgraphs for price history
vs alternatives: More comprehensive than single-DEX price feeds; enables cross-chain price analysis that individual DEX APIs cannot provide
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 DexPaprika at 25/100.
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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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