| Ecosystem |
| 1 |
| 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 5 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
This capability retrieves contextual information from a user's Gmail account using OAuth 2.0 for secure authentication. It employs a RESTful API design to fetch emails and metadata, allowing for seamless integration with other services in the MCP ecosystem. This approach ensures that the email data is accessed in real-time and can be processed dynamically based on user requests.
Unique: Utilizes OAuth 2.0 for secure, user-consented access to Gmail data, differentiating it from less secure methods.
vs alternatives: More secure and user-friendly than traditional API access methods that require hard-coded credentials.
This capability generates automated responses to emails by leveraging natural language processing models to analyze the content of incoming messages. It uses a template-based approach combined with machine learning to create contextually relevant replies, ensuring that responses are personalized and appropriate for the conversation. The integration with the MCP allows for dynamic adjustments based on user-defined rules.
Unique: Combines template-based responses with NLP for context-aware email replies, unlike simpler keyword-based systems.
vs alternatives: More nuanced and contextually aware than basic autoresponders that rely solely on keyword matching.
This capability summarizes entire email threads by analyzing the content of multiple messages in a conversation. It utilizes advanced NLP techniques to extract key points and generate concise summaries that capture the essence of discussions. The integration with the MCP allows for real-time processing and retrieval of summaries based on user queries.
Unique: Employs state-of-the-art summarization algorithms to condense email threads, which is more sophisticated than basic keyword extraction methods.
vs alternatives: Provides deeper insights and more accurate summaries than traditional summarization tools that rely on simple heuristics.
This capability processes attachments in emails by extracting and analyzing their content. It supports various file types, including PDFs and images, using specialized libraries for each format. The integration with the MCP allows for automated workflows that can trigger actions based on the content of attachments, such as saving files to cloud storage or generating reports.
Unique: Utilizes specialized libraries for different file formats, enabling comprehensive processing that goes beyond simple file downloads.
vs alternatives: More versatile in handling diverse attachment types compared to basic email clients that only allow file downloads.
This capability allows users to schedule emails for future sending and set reminders for follow-ups. It integrates with the Gmail API to manage sending times and uses a queue system to handle scheduled messages efficiently. Users can define rules for reminders based on email interactions, enhancing productivity and ensuring timely responses.
Unique: Implements a robust queuing system for managing scheduled emails, which is more reliable than ad-hoc scheduling methods.
vs alternatives: Offers a more reliable and user-friendly scheduling experience compared to basic email clients that lack advanced scheduling features.
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 gmail_mcp at 23/100. gmail_mcp leads on ecosystem, while Supabase is stronger on quality.
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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
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