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| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 10 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Initializes a Model Context Protocol server that communicates with AI assistants via StdioServerTransport over stdin/stdout, authenticating to CalDAV servers using environment variable credentials. The server registers tool handlers using @modelcontextprotocol/sdk and validates all incoming requests through Zod schemas before delegating to the underlying CalDAVClient, ensuring type-safe message serialization/deserialization across the MCP protocol boundary.
Unique: Uses @modelcontextprotocol/sdk's StdioServerTransport for direct stdin/stdout communication with AI assistants, avoiding HTTP overhead and enabling tight integration with Claude's native MCP support. Validates all tool inputs with Zod schemas before CalDAV delegation, providing type safety at the protocol boundary.
vs alternatives: Simpler deployment than REST-based calendar APIs because it eliminates HTTP server setup and uses MCP's standardized protocol, enabling direct integration with Claude without custom client code.
Exposes a list-calendars tool that queries the CalDAV server via ts-caldav's getCalendars() method, returning structured metadata for each calendar including display name, color, and calendar-specific properties. The tool validates no input parameters and returns a JSON array of calendar objects, enabling AI assistants to discover available calendars before performing event operations.
Unique: Directly wraps ts-caldav's getCalendars() method without caching or filtering, providing real-time calendar discovery. Zod schema validation ensures consistent output structure across CalDAV server implementations.
vs alternatives: More reliable than parsing calendar URLs manually because it uses the CalDAV protocol's standard PROPFIND discovery mechanism, handling server-specific variations automatically.
Implements a list-events tool that queries the CalDAV server for events within a specified date range using ts-caldav's getEvents() method. Accepts startDate and endDate parameters (ISO 8601 format), validates them with Zod schemas, and returns a structured JSON array of event objects including title, start/end times, description, and recurrence rules. Enables AI assistants to check calendar availability and retrieve event details for scheduling decisions.
Unique: Uses ts-caldav's getEvents() with CalDAV REPORT requests for server-side date filtering, reducing payload size compared to fetching all events and filtering client-side. Zod validates ISO 8601 date strings before passing to CalDAV client.
vs alternatives: More efficient than REST APIs that require fetching all events because CalDAV's REPORT method performs server-side filtering, reducing bandwidth and latency for large calendars.
Exposes a create-event tool that constructs new calendar events with title, start/end times, description, and optional recurrence rules (RRULE format). Validates all inputs using Zod schemas (date format, string length, RRULE syntax), then delegates to ts-caldav's createEvent() method which generates iCalendar (ICS) format and POSTs to the CalDAV server. Returns the created event's unique identifier (UID) and confirmation details, enabling AI assistants to schedule events with full iCalendar feature support.
Unique: Leverages ts-caldav's iCalendar (ICS) generation to support full RFC 5545 features including RRULE recurrence, avoiding custom event serialization. Zod schemas validate RRULE syntax and date ordering before CalDAV delegation, catching invalid inputs early.
vs alternatives: More feature-rich than simple REST event creation because it supports iCalendar's native recurrence rules (RRULE), enabling complex scheduling patterns without custom logic.
Implements a delete-event tool that removes calendar events by their unique identifier (UID). Accepts a single UID parameter, validates it with Zod schemas, and delegates to ts-caldav's deleteEvent() method which sends a DELETE request to the CalDAV server. Returns confirmation of deletion, enabling AI assistants to cancel or remove events from calendars with precise targeting.
Unique: Uses CalDAV's DELETE method with UID targeting, providing atomic event removal without requiring event re-fetching. Zod validates UID format before delegation, preventing malformed requests.
vs alternatives: More reliable than REST APIs that require event re-fetching before deletion because CalDAV's UID-based DELETE is idempotent and doesn't require state synchronization.
Implements runtime validation of all tool inputs using Zod schemas before delegating to CalDAVClient methods. Each tool (list-calendars, list-events, create-event, delete-event) has a corresponding Zod schema that validates parameter types, string lengths, date formats (ISO 8601), and RRULE syntax. Validation errors are caught and returned as structured MCP error responses, preventing invalid requests from reaching the CalDAV server and providing clear error messages to AI assistants.
Unique: Centralizes input validation at the MCP protocol boundary using Zod schemas, catching errors before CalDAV delegation. Provides structured validation errors that MCP clients can parse and present to users.
vs alternatives: More maintainable than ad-hoc validation because Zod schemas are declarative and reusable, reducing validation code duplication across tools.
Abstracts CalDAV protocol complexity by delegating all calendar operations to the ts-caldav library, which handles HTTP/CalDAV request construction, XML parsing, and iCalendar serialization. The MCP server registers tool handlers that call ts-caldav methods (getCalendars, getEvents, createEvent, deleteEvent), which internally manage PROPFIND/REPORT/PUT/DELETE requests, authentication headers, and response parsing. This abstraction eliminates the need for the MCP server to understand CalDAV protocol details.
Unique: Delegates all CalDAV protocol handling to ts-caldav, eliminating custom HTTP/XML code. The MCP server focuses purely on tool registration and input validation, keeping concerns separated.
vs alternatives: Simpler than implementing CalDAV protocol directly because ts-caldav handles PROPFIND/REPORT/PUT/DELETE request construction, XML parsing, and iCalendar serialization automatically.
Loads CalDAV server credentials (URL, username, password) from environment variables at server startup, avoiding hardcoded secrets in source code. The server reads CALDAV_URL, CALDAV_USERNAME, and CALDAV_PASSWORD from the process environment and passes them to the ts-caldav client initialization. This pattern enables secure deployment in containerized environments (Docker, Kubernetes) where secrets are injected at runtime.
Unique: Uses environment variables for credential injection, enabling secure deployment patterns in containerized environments without code changes. Credentials are loaded at startup and passed to ts-caldav client.
vs alternatives: More secure than hardcoded credentials and simpler than OAuth2 flows, making it ideal for internal automation and containerized deployments.
+2 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 CalDAV MCP at 22/100.
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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