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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 13 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Constructs and broadcasts transactions to the Algorand network by composing transaction objects with proper field validation, fee calculation, and signature handling. Integrates with Algorand SDK to serialize transactions and submit them through algod nodes, supporting atomic transaction groups and various transaction types (payment, asset transfer, application calls).
Unique: Exposes Algorand transaction composition as MCP tools with automatic field validation and fee estimation, allowing LLM agents to construct complex multi-transaction operations without direct SDK knowledge
vs alternatives: Provides higher-level transaction abstraction than raw Algorand SDK while maintaining full control, unlike web3.js which abstracts away transaction details
Retrieves real-time account information from the Algorand blockchain including ALGO balance, asset holdings, application state, and account metadata. Queries algod node's account endpoint and parses response to extract holdings, opted-in applications, and account flags, supporting both standard accounts and contract accounts.
Unique: Exposes account state as queryable MCP resources with structured parsing of holdings and application state, enabling LLM agents to reason about account composition without blockchain knowledge
vs alternatives: More comprehensive than simple balance queries — includes asset holdings and application state in single call, unlike basic RPC endpoints
Facilitates interaction with Algorand bridge protocols and liquidity pools (e.g., Tinyman, Pact) by composing swap transactions, managing liquidity positions, and handling bridge token wrapping/unwrapping. Supports automated market maker (AMM) calculations and bridge protocol-specific transaction patterns.
Unique: Abstracts AMM and bridge interactions as MCP tools with automatic price calculation and transaction composition, enabling LLM agents to execute DeFi operations without manual contract interaction
vs alternatives: Supports multiple pool protocols and bridges in unified interface, whereas individual tools require separate integrations per protocol
Enables participation in Algorand governance by managing voting keys, submitting governance votes, and tracking voting power. Handles voting key registration, vote submission for governance proposals, and reward claim transactions for governance participation.
Unique: Exposes governance participation as MCP tools with automatic voting key management and reward tracking, enabling LLM agents to participate in Algorand governance without manual key handling
vs alternatives: Provides end-to-end governance workflow from registration to reward claiming, whereas individual tools handle only single steps
Provides pre-built prompt templates and system instructions optimized for LLM reasoning about Algorand blockchain operations, transaction patterns, and smart contract interactions. Templates guide LLMs through transaction composition, error handling, and blockchain-specific decision-making with examples and best practices.
Unique: Provides Algorand-specific prompt templates as MCP resources, enabling LLM agents to reason about blockchain operations with domain-specific guidance built into the system context
vs alternatives: Offers blockchain-specific reasoning templates, whereas generic MCP servers provide no domain guidance
Fetches and caches metadata for Algorand Standard Assets (ASAs) and smart contracts (applications) including name, decimals, total supply, creator, and application state schema. Queries algod node's asset and application endpoints, with optional caching layer to reduce repeated network calls for frequently accessed assets.
Unique: Provides structured metadata resolution with optional caching layer, allowing MCP clients to enrich transaction data with human-readable asset information without repeated blockchain queries
vs alternatives: Combines asset and application metadata in unified interface with caching support, whereas individual SDK calls require separate requests per asset type
Queries transaction history for accounts or applications by scanning blockchain blocks and filtering transactions by sender, receiver, application ID, or asset ID. Uses algod indexer (if available) or falls back to block-by-block scanning, returning paginated transaction records with full details including inner transactions and application logs.
Unique: Provides dual-mode transaction retrieval with automatic fallback from indexer to block scanning, enabling both fast queries (with indexer) and offline-compatible queries (without indexer)
vs alternatives: Supports both indexer and block-scanning backends for flexibility, whereas most tools require indexer availability
Enables calling smart contract methods (applications) with typed arguments, reading application global and local state, and managing application opt-in/opt-out operations. Handles method signature parsing, argument encoding, and state key/value retrieval through algod endpoints, supporting both ABI-compliant and raw application calls.
Unique: Abstracts ABI-compliant method calling as MCP tools with automatic argument encoding and return value decoding, allowing LLM agents to interact with contracts using natural method signatures
vs alternatives: Supports both ABI-compliant and raw application calls for flexibility, whereas web3.js requires ABI definitions upfront
+5 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.
Supabase scores higher at 42/100 vs Algorand at 27/100.
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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
+1 more capabilities