| Ecosystem |
| 1 |
| 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 9 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Establishes and maintains persistent connections to Model Context Protocol (MCP) servers within n8n workflows. Implements MCP client protocol handshake, capability negotiation, and graceful connection teardown. Handles server discovery, authentication credential passing, and reconnection logic for long-running workflows.
Unique: Native MCP client implementation within n8n's node architecture, allowing workflows to treat MCP servers as first-class integration targets rather than generic HTTP endpoints. Implements full MCP protocol negotiation without requiring custom wrapper code.
vs alternatives: Tighter integration than generic HTTP nodes because it understands MCP protocol semantics (resources, tools, prompts) natively, enabling automatic capability discovery and structured tool invocation.
Executes tools exposed by connected MCP servers by marshaling arguments, handling async execution, and parsing structured responses. Implements MCP's tools/call protocol with automatic schema validation against server-declared tool signatures. Supports both simple scalar arguments and complex nested JSON payloads.
Unique: Implements MCP tools/call protocol with schema-aware argument validation, allowing n8n to catch argument mismatches before sending to the server. Automatically discovers tool signatures from server and exposes them as node parameters.
vs alternatives: More reliable than generic HTTP POST nodes because it validates arguments against server-declared schemas before execution, reducing round-trip failures and providing better error messages.
Discovers and retrieves resources exposed by MCP servers (documents, files, database records, etc.) through the resources/list and resources/read protocols. Implements hierarchical resource browsing with URI-based addressing and MIME type detection. Supports streaming large resources and caching resource metadata.
Unique: Implements MCP's resource protocol with URI-based addressing, allowing workflows to treat MCP resource servers as queryable knowledge stores rather than static data sources. Supports MIME type detection for automatic content type handling.
vs alternatives: More flexible than hardcoded file/database nodes because resources are dynamically discovered from the server, enabling workflows to adapt to changing resource availability without code changes.
Executes prompt templates defined on MCP servers, substituting workflow variables into template placeholders and returning rendered prompts. Implements MCP's prompts/get protocol with argument binding and template variable resolution. Enables reusable prompt engineering patterns stored server-side.
Unique: Enables server-side prompt template management through MCP, allowing prompt engineering to be decoupled from workflow definitions. Supports dynamic argument binding at workflow runtime.
vs alternatives: Better than hardcoded prompts in workflow nodes because templates can be updated on the server without redeploying workflows, and multiple workflows can share the same prompt definitions.
Queries connected MCP servers to discover available capabilities (tools, resources, prompts) and their schemas. Implements MCP's initialize handshake and capability advertisement protocol. Exposes discovered capabilities as node parameters and workflow options, enabling dynamic workflow configuration.
Unique: Implements full MCP capability negotiation protocol, allowing n8n to dynamically understand and expose server capabilities without hardcoded tool lists. Schemas are discovered at runtime and used to validate workflow configuration.
vs alternatives: More maintainable than manually documenting available tools because capability lists are always in sync with the actual server, reducing configuration drift and documentation burden.
Marshals n8n workflow context (previous step outputs, global variables, trigger data) into MCP tool/prompt arguments with automatic type coercion and JSON path resolution. Implements expression evaluation for dynamic argument construction and supports both simple scalar and complex nested object binding.
Unique: Integrates n8n's expression language with MCP argument marshaling, allowing workflows to use n8n's full expression syntax (conditionals, filters, transformations) when constructing tool arguments.
vs alternatives: More powerful than static argument mapping because it supports dynamic expressions, enabling workflows to adapt tool arguments based on runtime conditions without additional transformation steps.
Captures and parses error responses from MCP servers, extracting error codes, messages, and context. Implements error propagation to n8n's workflow error handling system with detailed error information. Supports retry logic configuration and error recovery patterns.
Unique: Parses MCP protocol error responses and maps them to n8n's error handling system, allowing workflows to distinguish between transient and permanent failures based on server error codes.
vs alternatives: Better error visibility than generic HTTP nodes because it understands MCP error semantics and provides structured error information that can be used for conditional error handling.
Enables workflows to connect to and orchestrate multiple MCP servers simultaneously, managing separate connections and routing tool calls to appropriate servers. Implements server selection logic and handles cross-server data flow. Supports server failover and load balancing across multiple instances.
Unique: Allows workflows to manage multiple independent MCP server connections within a single workflow execution context, enabling tool orchestration across distributed MCP infrastructure.
vs alternatives: More flexible than single-server integrations because it enables workflows to combine capabilities from multiple specialized servers without requiring a central MCP proxy.
+1 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 n8n-nodes-mcp at 25/100.
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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