| 0 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 12 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes HubSpot's REST API endpoints as standardized MCP tools, translating HubSpot resource operations (contacts, deals, companies, etc.) into a schema-based function registry that MCP clients can discover and invoke. Uses MCP's tool definition protocol to wrap HubSpot API calls with standardized input/output schemas, enabling any MCP-compatible client (Claude, custom agents) to interact with HubSpot without direct API knowledge.
Unique: Native MCP server implementation specifically for HubSpot, translating HubSpot's REST API surface into MCP's standardized tool schema format with automatic schema generation from HubSpot's API definitions
vs alternatives: Purpose-built for HubSpot + MCP ecosystem vs generic REST API wrappers, eliminating custom schema definition and providing HubSpot-specific error handling and authentication patterns
Manages HubSpot API authentication by accepting and validating API keys, automatically injecting credentials into outbound requests, and handling token refresh/expiration. Implements secure credential storage patterns appropriate for MCP server contexts, ensuring API keys are not leaked in logs or tool definitions while maintaining stateful authentication across multiple tool invocations.
Unique: Implements MCP-aware credential handling that keeps API keys out of tool schemas and client-visible definitions, using server-side injection patterns to prevent credential exposure in MCP tool discovery responses
vs alternatives: More secure than generic API wrapper libraries because it enforces credential isolation at the MCP protocol layer, preventing accidental leakage through tool definitions or client logs
Exposes HubSpot's custom property and field schema definitions as MCP tools, allowing LLM agents to discover available properties, their types, and validation rules for each object type. Implements schema introspection through MCP tool calls, returning property metadata (name, type, required, options for enums, etc.). Enables agents to validate property values before attempting to create or update objects.
Unique: Provides MCP tools for HubSpot schema introspection, enabling LLM agents to discover and validate against HubSpot's property definitions without requiring hardcoded schema knowledge
vs alternatives: More flexible than hardcoded property lists because schema is dynamically retrieved from HubSpot, and more reliable than prompt-engineering property validation because tools provide authoritative schema information
Exposes HubSpot Workflows API as MCP tools for triggering custom workflows and automations. Implements workflow invocation through MCP tool calls, passing workflow input parameters and receiving execution status. Supports triggering workflows based on object changes or external events, enabling AI agents to orchestrate multi-step HubSpot automations.
Unique: Provides MCP tools for HubSpot workflow invocation, allowing LLM agents to trigger complex automations without requiring knowledge of HubSpot's workflow execution API or parameter schemas
vs alternatives: More powerful than individual object operations because workflow tools enable multi-step automations, and more flexible than hardcoded workflows because agents can decide which workflows to trigger based on context
Provides Create, Read, Update, Delete operations for HubSpot resources (contacts, deals, companies, tickets, etc.) through MCP tool definitions with schema validation. Each operation is exposed as a distinct MCP tool with input validation, error handling, and HubSpot-specific response normalization, allowing clients to perform standard data mutations without understanding HubSpot's API versioning or endpoint structure.
Unique: Normalizes HubSpot's heterogeneous API endpoints (different schemas for contacts vs deals vs companies) into a consistent CRUD tool pattern, abstracting away HubSpot's API versioning and endpoint inconsistencies
vs alternatives: Simpler for agents than raw API calls because it provides schema validation and error normalization, reducing agent hallucination around HubSpot's complex property naming conventions
Translates natural search criteria (e.g., 'contacts with email domain @acme.com') into HubSpot's filter API syntax, supporting property-based filtering, date ranges, and relationship queries. Implements query builder patterns that map common search intents to HubSpot's filter language, handling edge cases like custom properties and enum-based fields without requiring clients to know HubSpot's filter syntax.
Unique: Implements a query translation layer that converts high-level search intents into HubSpot's filter API format, reducing the cognitive load on agents to understand HubSpot's filter syntax and property naming conventions
vs alternatives: More agent-friendly than raw HubSpot API filtering because it abstracts filter syntax, allowing agents to express searches in natural terms rather than HubSpot's specific filter language
Automatically generates MCP tool schemas for HubSpot resources based on HubSpot's API definitions, exposing available operations, required/optional properties, and valid enum values. Implements schema introspection patterns that allow MCP clients to discover available tools and their input/output contracts without hardcoding, enabling dynamic tool registration and client-side validation.
Unique: Generates MCP-compliant tool schemas directly from HubSpot's API definitions, enabling dynamic discovery without manual schema definition, and includes property-level metadata (types, enums, descriptions) for client-side validation
vs alternatives: More maintainable than hardcoded tool schemas because it derives definitions from HubSpot's API, reducing drift between server capabilities and client expectations
Catches HubSpot API errors (rate limits, invalid properties, authentication failures) and translates them into human-readable error messages suitable for agent consumption. Implements retry logic for transient failures (rate limits, timeouts) and provides structured error responses that help agents understand what went wrong and how to recover.
Unique: Translates HubSpot's API error responses into agent-friendly messages with recovery suggestions, implementing automatic retry logic for transient failures without requiring agent-side error handling
vs alternatives: More resilient than raw API calls because it abstracts HubSpot's error semantics and implements automatic retry logic, reducing agent hallucination and improving reliability
+4 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 @hubspot/mcp-server at 35/100.
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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