| Ecosystem |
| 1 |
| 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
A2A-Swap implements a constant-product AMM model (x·y=k) using a purely functional programming approach, allowing for efficient and predictable liquidity provision. Each trade is executed through a single typed function call, ensuring that all operations are deterministic and can be easily integrated into AI agents or trading bots without the need for a UI. This architecture minimizes overhead and maximizes performance for on-chain programs.
Unique: Utilizes a purely functional programming paradigm to ensure that all operations are stateless and can be easily composed, which is distinct from many AMMs that rely on mutable state.
vs alternatives: More efficient for AI integrations than traditional AMMs that require complex state management and UI interactions.
A2A-Swap allows for the execution of trades and liquidity operations through typed function calls, which are designed to be explicit and self-documenting. This approach reduces the risk of errors commonly associated with loosely typed languages and ensures that developers can easily understand the expected inputs and outputs of each function. The use of a strict type system enhances the reliability of on-chain interactions.
Unique: The implementation of a strict type system for function calls enhances reliability and developer experience compared to other AMMs that may not enforce type safety.
vs alternatives: Offers better type safety than many competing AMMs that rely on dynamic typing, reducing runtime errors.
A2A-Swap provides a command-line interface (CLI) that allows users to interact with the AMM using simple commands. This design choice eliminates the need for a graphical user interface, making it lightweight and suitable for automated scripts or integration into other tools. The CLI commands are structured to mirror the underlying function calls, providing a consistent experience across different interaction methods.
Unique: The CLI is designed to be a direct mapping of the underlying function calls, providing a seamless transition between manual and automated interactions.
vs alternatives: More streamlined for automation than AMMs with complex UIs, allowing for easier script integration.
A2A-Swap is designed to be easily integrated into on-chain programs, allowing developers to create custom trading strategies or liquidity management solutions. The architecture supports direct function calls from smart contracts, enabling seamless interaction with the AMM without needing intermediary layers. This direct integration reduces latency and enhances performance for on-chain applications.
Unique: The architecture allows direct function calls from smart contracts, avoiding the overhead of external API calls, which is common in many AMM implementations.
vs alternatives: Faster and more efficient than AMMs that require external API calls for on-chain interactions.
A2A-Swap allows users to manage liquidity provision through a series of typed function calls that enable adding, removing, and adjusting liquidity in real-time. This capability is crucial for traders and bots that need to respond quickly to market changes. The system is designed to ensure that liquidity operations are atomic and can be executed without the risk of partial failures.
Unique: The atomic nature of liquidity operations ensures that all changes are applied consistently, which is a critical feature for maintaining market stability.
vs alternatives: More reliable than AMMs that allow for partial liquidity updates, which can lead to inconsistencies.
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 mcp-a2a-swap at 26/100.
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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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