Supabase ranks higher at 42/100 vs Nebula-Block-Data/nebulablock-mcp-server at 25/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | Nebula-Block-Data/nebulablock-mcp-server | Supabase |
|---|---|---|
| Type | MCP Server | MCP Server |
| UnfragileRank | 25/100 | 42/100 |
| Adoption | 0 | 0 |
| Quality |
| 0 |
| 0 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 8 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes NebulaBlock's blockchain data APIs as standardized MCP tools that Claude and other LLM clients can invoke directly. Uses fastmcp library to wrap REST/GraphQL endpoints into a tool registry with schema-based function calling, enabling LLMs to query on-chain data (transactions, balances, smart contracts) without direct API knowledge or credential management.
Unique: Bridges NebulaBlock's proprietary blockchain indexing APIs into the MCP protocol via fastmcp, allowing LLMs to treat on-chain data as native tools without custom SDK integration or credential exposure to the LLM context window.
vs alternatives: Simpler than building custom blockchain agent tools because it leverages fastmcp's schema generation and MCP's standardized tool protocol, reducing boilerplate compared to manual OpenAI function-calling or Anthropic tool-use implementations.
Implements MCP server bootstrap logic that discovers, validates, and registers NebulaBlock API endpoints as callable tools at startup. Uses fastmcp's decorator-based tool registration pattern to map API methods to MCP tool schemas with automatic parameter validation, type coercion, and error handling, enabling seamless client connection without manual schema definition.
Unique: Uses fastmcp's decorator-based tool registration to automatically generate MCP-compliant tool schemas from Python function signatures, eliminating manual JSON schema writing and enabling type-safe tool invocation with minimal boilerplate.
vs alternatives: Faster to deploy than hand-crafted MCP servers because fastmcp handles schema generation and validation automatically, whereas building raw MCP servers requires explicit JSON schema definition and client protocol handling.
Manages NebulaBlock API credentials and request context on the server side, preventing credential exposure to LLM clients or context windows. Credentials are stored server-side and injected into API requests transparently, ensuring LLMs interact with blockchain data without handling sensitive authentication material or making direct API calls.
Unique: Implements server-side credential injection pattern where NebulaBlock API keys are never exposed to LLM clients or context windows; credentials are stored and managed exclusively on the MCP server, with all API calls proxied through authenticated server endpoints.
vs alternatives: More secure than passing API keys to LLMs directly (as some naive integrations do) because credentials remain server-side and isolated from the LLM's context, reducing attack surface and enabling centralized credential rotation.
Translates between MCP protocol messages and NebulaBlock API calls, handling serialization, deserialization, and error mapping. Converts LLM tool invocations (MCP CallTool requests) into properly formatted NebulaBlock API requests, then maps API responses and errors back to MCP-compliant formats with structured error messages, timeouts, and retry logic.
Unique: Implements bidirectional protocol translation between MCP's tool invocation semantics and NebulaBlock's REST/GraphQL API contracts, with explicit error mapping that converts API failures into MCP-compliant error responses that LLMs can interpret and act upon.
vs alternatives: More robust than direct API wrapping because it handles protocol-level concerns (serialization, error codes, timeouts) that raw API clients ignore, reducing the likelihood of protocol violations or silent failures.
Provides tools for querying and aggregating data across multiple blockchain networks or NebulaBlock data sources through a unified MCP interface. Enables LLMs to invoke separate tools for different chains (Ethereum, Polygon, etc.) and correlate results, with each tool maintaining its own API endpoint and credential context but sharing the same MCP protocol surface.
Unique: Exposes multiple NebulaBlock API endpoints (one per blockchain) as distinct MCP tools with shared protocol semantics, allowing LLMs to query different chains through a unified interface while maintaining separate credentials and rate-limit contexts per chain.
vs alternatives: More flexible than monolithic multi-chain APIs because each chain's tool can be independently versioned, rate-limited, and authenticated, whereas unified APIs require coordinating all chains through a single endpoint.
Exposes NebulaBlock's event or subscription APIs as MCP tools that allow LLMs to request real-time blockchain data (new transactions, contract events, price updates). Tools may return streaming data or poll-based updates, with fastmcp handling the transport of event data back to the LLM client through MCP's message protocol.
Unique: Bridges NebulaBlock's event APIs into MCP's tool protocol, enabling LLMs to subscribe to and consume real-time blockchain events through standard tool invocations, with fastmcp handling the transport of streaming data through MCP messages.
vs alternatives: More accessible than building custom WebSocket clients because MCP tools abstract the streaming transport, allowing LLMs to consume events through the same tool interface as static queries.
Automatically generates and enforces MCP tool schemas from NebulaBlock API specifications, validating LLM-provided parameters against expected types, ranges, and formats before invoking the API. Uses fastmcp's schema generation to create JSON schemas for each tool, with runtime validation that rejects invalid parameters and provides structured error feedback to the LLM.
Unique: Leverages fastmcp's automatic schema generation from Python type hints to create MCP-compliant tool schemas that enforce parameter validation at the protocol level, preventing invalid requests from reaching the NebulaBlock API.
vs alternatives: More efficient than server-side validation because schema validation happens before tool invocation, reducing API calls and providing immediate feedback to the LLM, whereas post-invocation validation wastes API quota.
Implements per-tool rate limiting and quota tracking for NebulaBlock API calls, tracking invocation counts and enforcing limits to prevent quota exhaustion. Maintains request counters per tool and returns rate-limit status to the LLM client, allowing agents to throttle or defer requests when approaching limits.
Unique: Implements server-side rate limiting at the MCP tool level, tracking per-tool invocation counts and enforcing quotas before API calls, enabling cost control and preventing quota exhaustion from uncontrolled LLM agent behavior.
vs alternatives: More granular than API-level rate limiting because it tracks and limits at the tool invocation level, allowing different tools to have different quotas and providing visibility into which tools consume the most quota.
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 Nebula-Block-Data/nebulablock-mcp-server 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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