| 0 |
| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes web search functionality through the Model Context Protocol (MCP) standard, allowing Claude and other MCP-compatible clients to invoke search queries as tools. Implements MCP server architecture with tool definition schemas that declare search parameters, enabling LLM agents to autonomously decide when and how to search the web without requiring direct API integration in client code.
Unique: Implements MCP server pattern specifically for web search, allowing declarative tool registration with Claude rather than requiring custom integration code — uses MCP's standardized tool schema to expose search as a first-class capability that agents can discover and invoke autonomously
vs alternatives: Simpler than building custom Claude tool integrations because it leverages MCP's standardized protocol; more flexible than hardcoded web search because agents can decide when to search based on context
Defines and registers web search as an MCP tool by declaring its parameters, return types, and descriptions in the MCP tool schema format. The server exposes tool metadata (name, description, input schema with JSON Schema validation) that MCP clients parse to understand how to invoke the search capability, enabling automatic tool discovery and validation without manual configuration.
Unique: Uses MCP's standardized tool schema format rather than custom JSON or YAML — enables interoperability across any MCP-compatible client without adapter code, and allows Claude to understand tool capabilities through protocol-level metadata rather than prompt injection
vs alternatives: More maintainable than prompt-based tool descriptions because schema changes are version-controlled and validated; more discoverable than REST APIs because clients can introspect available tools at runtime
Implements the MCP server lifecycle including initialization, request handling, and graceful shutdown. The server listens for MCP protocol messages (tool calls, resource requests), routes them to appropriate handlers, and returns responses in MCP format. Manages connection state and error handling to ensure reliable communication between MCP clients and the search backend.
Unique: Implements MCP server pattern with full protocol compliance — handles MCP's JSON-RPC message format, tool invocation routing, and response serialization rather than exposing raw HTTP endpoints, enabling seamless integration with MCP-aware clients
vs alternatives: More reliable than custom HTTP wrappers because MCP protocol handles versioning and error codes; more maintainable than REST APIs because protocol changes are managed by the MCP spec rather than custom versioning logic
Accepts a search query string from an MCP client, executes it against a web search backend (likely Brave Search, Google Custom Search, or similar), and formats the results into a structured response. Handles query normalization, backend API communication, result parsing, and formatting into a consistent JSON structure that includes title, URL, snippet, and metadata for each result.
Unique: Abstracts away search provider implementation details behind the MCP tool interface — clients don't need to know whether results come from Brave, Google, or another provider, and the backend can be swapped without changing client code
vs alternatives: More flexible than hardcoded search integrations because the backend provider can be configured or swapped; more reliable than direct API calls because MCP protocol handles retries and error standardization
Enables Claude (or other MCP-compatible LLM agents) to autonomously invoke the web search tool as part of its reasoning process. Claude's tool-use capability discovers the search tool through MCP metadata, decides when to invoke it based on context, formats the search query, and integrates results back into its reasoning loop. The agent can chain multiple searches and use results to inform subsequent actions.
Unique: Integrates with Claude's native tool-use capability through MCP protocol — Claude automatically discovers and invokes the search tool without requiring custom prompts or integration code, and can chain searches with other tools in multi-step workflows
vs alternatives: More seamless than custom Claude integrations because it uses Claude's built-in tool-calling mechanism; more flexible than hardcoded search because Claude decides when to search based on reasoning rather than explicit triggers
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 miyami-websearch-mcp at 24/100. miyami-websearch-mcp leads on ecosystem, while Supabase is stronger on quality.
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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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