| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Constructs properly-formatted UTM links by accepting campaign parameters (source, medium, campaign, content, term) and appending them as query strings to base URLs. Validates parameter syntax and ensures URL encoding compliance, supporting both simple single-link generation and batch operations for multi-channel campaigns.
Unique: Integrates link building with downstream validation in a single preflight command, rather than treating link generation as a separate step — allows developers to validate that generated links actually resolve and contain proper metadata before campaign launch
vs alternatives: Faster than manual UTM builders or spreadsheet-based approaches because it combines generation, validation, and metadata inspection in one CLI invocation without context switching
Follows HTTP redirect chains (301, 302, 307, 308) to resolve final destination URLs, detecting redirect loops and validating that campaign links actually reach intended landing pages. Implements configurable timeout and hop limits to prevent infinite redirect scenarios, returning both the final URL and the complete redirect chain for debugging.
Unique: Combines redirect resolution with metadata inspection (OG tags, Twitter Cards) in a single validation pass, allowing developers to catch both broken redirects AND missing social metadata in one command rather than running separate tools
vs alternatives: More comprehensive than simple HTTP status checkers because it resolves the full redirect chain and validates final-destination metadata, not just the initial response code
Parses HTML responses to extract Open Graph (og:title, og:description, og:image, og:url) and Twitter Card (twitter:card, twitter:title, twitter:description, twitter:image) meta tags. Validates that required tags are present, image URLs are accessible, and dimensions meet platform specifications (e.g., Twitter image minimum 200x200px). Returns structured metadata report with validation status.
Unique: Validates both presence AND correctness of social metadata (e.g., image dimensions, URL accessibility) rather than just checking if tags exist, providing actionable feedback for fixing social preview issues
vs alternatives: More thorough than browser-based social preview tools because it validates metadata programmatically and can batch-check hundreds of URLs, making it suitable for CI/CD integration
Analyzes landing pages for mobile optimization signals including viewport meta tag presence, responsive CSS media queries, touch-friendly button sizes (minimum 44x44px), font readability (minimum 16px base), and viewport configuration. Returns structured report with specific issues and recommendations for improving mobile experience.
Unique: Combines multiple mobile readiness signals (viewport, CSS, font sizes, button dimensions) into a single validation report rather than checking each in isolation, providing a holistic mobile readiness score
vs alternatives: Faster than running Google Mobile-Friendly Test or Lighthouse for batch validation because it performs static analysis without rendering, making it suitable for pre-launch validation of dozens of campaign variants
Orchestrates all validation capabilities (redirect resolution, OG/Twitter metadata extraction, mobile readiness assessment) in a single CLI command, executing them in parallel or sequence based on configuration. Aggregates results into a comprehensive pre-launch report with pass/fail status, specific issues, and actionable remediation steps. Supports configuration files for reusable validation profiles.
Unique: Combines link building, validation, and inspection into a single atomic operation with configuration-driven profiles, allowing teams to define once and reuse validation standards across all campaigns rather than manually running separate tools
vs alternatives: More efficient than running separate validation tools because it batches network requests and aggregates results into a single report, reducing total validation time by 60-70% compared to sequential tool execution
Exposes campaign link building and validation capabilities as MCP server resources and tools, allowing AI agents and LLM-powered applications to programmatically generate UTM links, validate destinations, and inspect metadata. Implements MCP resource types for campaign configurations and validation results, enabling AI systems to reason about campaign health and suggest optimizations.
Unique: Implements MCP server pattern to expose campaign validation as composable tools for AI agents, enabling LLMs to reason about campaign health and suggest optimizations rather than just reporting validation results
vs alternatives: Enables AI-assisted campaign optimization that would be impossible with CLI-only tools, allowing LLMs to analyze validation results and suggest improvements (e.g., 'your OG image is too small, consider 1200x630px')
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 MissingLinkz 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
+1 more capabilities