Supabase ranks higher at 42/100 vs @cloudflare/mcp-server-cloudflare at 31/100. Capability-level comparison backed by match graph evidence from real search data.
| Feature | @cloudflare/mcp-server-cloudflare | Supabase |
|---|---|---|
| Type | MCP Server | MCP Server |
| UnfragileRank | 31/100 | 42/100 |
| Adoption | 0 | 0 |
| Quality |
| 0 |
| 0 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 14 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Implements the Model Context Protocol (MCP) specification as a production-grade server deployed on Cloudflare Workers, using HTTP streaming via /mcp endpoint with streamble-http transport for bidirectional communication between LLMs and Cloudflare services. Handles tool discovery, prompt templates, and resource management through standardized MCP message framing with automatic serialization/deserialization of tool schemas and responses.
Unique: Uses Cloudflare Workers as the deployment platform for MCP servers, enabling global edge distribution and automatic scaling without managing infrastructure; implements HTTP streaming transport with streamble-http instead of SSE, providing lower latency and better connection reliability for long-running operations.
vs alternatives: Faster and more scalable than self-hosted MCP servers because it leverages Cloudflare's global edge network and Workers runtime, eliminating cold-start penalties and providing automatic failover across regions.
Provides two authentication pathways: OAuth 2.0 flow for user-based access (interactive authorization with Cloudflare account) and API token mode for programmatic access (service-to-service authentication). Implements secure credential validation, token refresh, and user state management through Durable Objects for session persistence, with automatic credential injection into downstream Cloudflare API calls.
Unique: Implements dual authentication modes (OAuth + API tokens) with unified credential injection into all downstream Cloudflare API calls, using Durable Objects for distributed session state rather than in-memory caching, enabling multi-region consistency and automatic failover.
vs alternatives: More flexible than single-mode authentication because it supports both interactive user flows and programmatic service-to-service access without requiring separate infrastructure or credential management systems.
Implements a specialized MCP server for searching Cloudflare documentation and code examples using semantic search powered by Vectorize embeddings. Enables LLMs to find relevant documentation sections, API examples, and best practices based on natural language queries, with support for filtering by documentation category (Workers, Pages, API, etc.) and code language.
Unique: Provides semantic search over Cloudflare's entire documentation corpus using Vectorize embeddings, enabling LLMs to find relevant docs and code examples through natural language queries without keyword matching.
vs alternatives: More effective than keyword-based documentation search because it understands semantic intent; more integrated than external search tools because it's optimized for Cloudflare-specific content and terminology.
Exposes Cloudflare Browser Rendering capabilities through MCP tools for rendering web pages, capturing screenshots, and extracting page content. Implements headless browser automation with support for JavaScript execution, form interaction, and dynamic content rendering, providing LLMs with the ability to analyze visual content and interact with web applications.
Unique: Integrates Cloudflare's native Browser Rendering service through MCP, enabling LLMs to render and analyze web pages without external browser automation tools; supports JavaScript execution and dynamic content rendering.
vs alternatives: More efficient than external browser automation because it's deployed on Cloudflare's edge network, reducing latency and eliminating the need to manage separate browser infrastructure.
Provides shared packages (@repo/mcp-common, @repo/mcp-observability, @repo/eval-tools) that all MCP servers depend on for authentication, metrics collection, and testing. Implements centralized observability through structured logging, distributed tracing, and metrics aggregation, with support for monitoring tool execution latency, error rates, and authentication failures across all servers.
Unique: Provides a unified observability framework across all MCP servers through shared packages, enabling centralized monitoring and debugging without per-server instrumentation; implements structured logging and metrics collection at the framework level.
vs alternatives: More cohesive than per-server observability because it provides consistent metrics, logging, and tracing across all servers; reduces operational overhead by centralizing monitoring infrastructure.
Implements a production monorepo structure using pnpm workspaces for dependency management and Turbo for build orchestration, enabling efficient development and deployment of 15+ independent MCP servers. Provides shared build configuration, testing infrastructure (Vitest), and deployment pipelines that reduce duplication and ensure consistency across all servers.
Unique: Uses pnpm workspaces and Turbo to manage 15+ independent MCP servers in a single monorepo, enabling efficient builds and deployments through shared configuration and incremental compilation; provides scaffolding for new servers.
vs alternatives: More efficient than separate repositories because it enables code sharing, consistent tooling, and parallel builds; more maintainable than manual build scripts because Turbo handles dependency ordering and caching automatically.
Maintains a centralized registry of 100+ tools across 15+ specialized MCP servers (Workers Observability, DNS Analytics, AI Gateway, etc.), each with JSON Schema definitions for parameters and return types. Implements automatic tool discovery, schema validation, and routing to the appropriate server based on tool namespace, with support for tool categorization (Common Tools, Container Management, Observability, Workers Management, AI & Data Tools).
Unique: Implements a unified tool registry across 15+ independent MCP servers with automatic schema generation from TypeScript interfaces, enabling LLMs to discover and invoke tools across multiple Cloudflare domains (Workers, DNS, AI Gateway, etc.) without manual tool definition.
vs alternatives: More comprehensive than single-domain MCP servers because it exposes the entire Cloudflare platform surface through a single registry, reducing the number of MCP connections an LLM client needs to maintain.
Exposes Cloudflare Workers runtime observability through MCP tools that query Analytics Engine, tail real-time logs, retrieve error traces, and analyze performance metrics. Implements direct integration with Cloudflare's Analytics Engine for structured query execution and Durable Objects for log streaming, providing LLMs with visibility into Worker execution, CPU time, memory usage, and request/error patterns.
Unique: Integrates with Cloudflare's Analytics Engine for structured metric queries and Durable Objects for real-time log streaming, enabling LLMs to access both historical analytics and live execution traces without polling or external logging infrastructure.
vs alternatives: More integrated than generic log aggregation tools because it understands Cloudflare Workers semantics (CPU time, memory, request context) and provides both real-time and historical data through a single MCP interface.
+6 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 @cloudflare/mcp-server-cloudflare at 31/100.
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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