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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Queries Bluesky's public API to retrieve feed data by connecting to the AT Protocol endpoints, parsing JSON responses, and materializing feed posts with metadata (author, timestamp, engagement metrics). Implements direct HTTP client integration with Bluesky's REST API rather than using a third-party SDK wrapper, enabling low-latency feed access without abstraction overhead.
Unique: Direct AT Protocol API integration without SDK abstraction layer, enabling tight control over request/response handling and minimal latency for context server use cases where feed data is materialized into MCP resources
vs alternatives: Lower overhead than Bluesky SDK wrappers because it speaks directly to AT Protocol endpoints, making it ideal for stateless context servers that need fast feed materialization
Implements search capability against Bluesky posts using the AT Protocol search endpoints, supporting keyword matching, author filtering, and temporal range queries. Returns ranked post results with relevance scoring and allows filtering by engagement metrics (likes, reposts) or post type (text, links, media). Uses query parameter composition to construct AT Protocol-compatible search requests.
Unique: Wraps Bluesky's native search API with composable filter chains (author, date, engagement) that can be combined without multiple round-trips, reducing latency for complex queries in context server scenarios
vs alternatives: More efficient than client-side filtering because it pushes predicates to the Bluesky API layer, avoiding transfer of irrelevant posts and reducing bandwidth
Exposes Bluesky feeds and posts as MCP resources that can be consumed by LLM agents and context servers. Implements MCP resource handlers that wrap feed/post queries and present results as structured, queryable resources with standardized schemas. Enables LLM agents to access Bluesky data through a unified MCP interface without direct API knowledge.
Unique: Bridges Bluesky API and MCP protocol by implementing resource handlers that translate AT Protocol queries into MCP-compatible responses, enabling seamless LLM agent access to Bluesky without custom tool implementations
vs alternatives: More composable than custom tool definitions because it uses MCP's standardized resource model, allowing agents to discover and query Bluesky data through a consistent interface
Materializes Bluesky feed and post data into an in-memory or persistent cache, enabling fast repeated access without hitting rate limits. Implements TTL-based cache invalidation and optional persistent storage (file, database) for context that needs to survive server restarts. Supports cache warming by pre-fetching feeds on startup or on a schedule.
Unique: Implements multi-tier caching (in-memory + optional persistent) with configurable TTL and cache warming, reducing API load for context servers that serve repeated queries over the same feeds
vs alternatives: More efficient than naive repeated API calls because it batches cache updates and supports pre-warming, reducing latency for common queries by 10-100x
Handles Bluesky/AT Protocol authentication by managing session tokens, refreshing credentials, and maintaining authenticated HTTP clients. Supports both user credentials (username/password) and app-specific tokens. Implements automatic token refresh to prevent session expiration during long-running operations.
Unique: Wraps AT Protocol's session token lifecycle with automatic refresh logic, eliminating the need for callers to manually handle token expiration or re-authentication
vs alternatives: Simpler than manual token management because it transparently refreshes credentials before expiration, reducing 401 errors and retry logic in calling code
Extracts and normalizes metadata from Bluesky posts (author, timestamp, engagement metrics, media attachments, reply chains) into a consistent schema. Handles AT Protocol's nested data structures and converts them to flat, queryable formats. Supports extraction of embedded links, hashtags, and mentions for downstream processing.
Unique: Implements AT Protocol-aware parsing that handles Bluesky's nested facet and embed structures, converting them to flat, queryable schemas without losing information
vs alternatives: More robust than generic JSON flattening because it understands AT Protocol semantics (facets, embeds, reply refs) and preserves structured relationships
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 Bluesky at 20/100.
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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