| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability allows users to perform complex, filtered searches across various entities in the Autotask PSA, such as tickets, projects, and contacts. It employs a query-building interface that dynamically constructs search parameters based on user input, leveraging the underlying API to fetch relevant results efficiently. The integration with Autotask's API ensures that the search is both fast and reliable, providing comprehensive data for reporting and analysis.
Unique: Utilizes a dynamic query-building mechanism that adapts to user inputs, enhancing search relevance and speed.
vs alternatives: More flexible than standard Autotask search interfaces, allowing for complex filtering without needing to manually set parameters.
This capability automates the mapping of internal IDs to user-friendly names for entities like companies and contacts. It uses a caching mechanism to store previously resolved mappings, reducing the need for repeated API calls and improving performance. When a user requests data, the system checks the cache first before querying the Autotask API, ensuring faster response times and a smoother user experience.
Unique: Incorporates a caching layer that minimizes API calls for ID resolution, enhancing performance and user experience.
vs alternatives: Faster than traditional methods that require constant API lookups for ID resolution.
This capability enables users to log time against specific tickets and manage detailed notes and attachments. It integrates with the Autotask API to update ticket information in real-time, ensuring that all changes are reflected immediately. Users can attach files and notes directly to tickets, which are then stored in a structured format for easy retrieval and reporting.
Unique: Offers real-time updates and attachments directly linked to tickets, enhancing context and accountability.
vs alternatives: More integrated than standalone time-tracking tools, as it ties directly into ticket management.
This capability allows users to create, update, and manage invoices and quotes directly through the Autotask API. It provides a user-friendly interface for entering details, which are then validated against existing data to ensure accuracy. The system supports batch operations for efficiency, allowing users to handle multiple invoices or quotes simultaneously.
Unique: Integrates batch processing capabilities for invoices and quotes, streamlining the billing workflow significantly.
vs alternatives: More efficient than manual entry systems, as it allows for bulk updates and validations.
This capability provides users with the ability to create, update, and manage tasks associated with tickets and projects. It utilizes the Autotask API to ensure that all task-related data is synchronized in real-time, allowing for seamless collaboration among team members. Users can set deadlines, assign tasks, and track progress directly from the interface.
Unique: Real-time synchronization with the Autotask API ensures that all task updates are immediately reflected across the platform.
vs alternatives: More integrated than standalone task management tools, as it connects directly to ticketing and project workflows.
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 Autotask PSA at 32/100.
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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