| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 6 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Exposes Figma API endpoints as MCP tools, allowing LLM agents to query document structure, layers, components, and metadata through a standardized protocol interface. Implements MCP server specification to translate Figma REST API calls into tool definitions that language models can invoke, enabling agents to understand design file hierarchies without direct API knowledge.
Unique: Bridges Figma REST API and MCP protocol specification, allowing LLM agents to treat Figma documents as queryable tools without requiring agents to understand HTTP semantics or API authentication — the MCP server handles credential management and protocol translation transparently
vs alternatives: Unlike raw Figma API integration, MCP protocol standardization enables drop-in compatibility with any MCP-compatible LLM client (Claude, custom agents) without client-side API binding code
Automatically generates MCP tool definitions that map Figma API endpoints to callable functions with proper parameter schemas, type hints, and descriptions. Uses MCP server specification to define tools with JSON Schema validation, allowing LLM clients to understand available operations and constraints before invocation.
Unique: Implements MCP tool schema generation specifically for Figma's hierarchical document model, mapping complex nested API responses to flat tool parameters that LLMs can reason about — avoids exposing raw API complexity to agents
vs alternatives: Provides schema-driven tool definition vs manual tool registration, reducing integration boilerplate and enabling automatic validation of agent requests against Figma API constraints
Handles Figma API authentication through MCP server configuration, supporting personal access tokens and OAuth flows. Manages credential lifecycle (storage, refresh, expiration) and injects authentication headers into all Figma API requests transparently, isolating clients from credential handling complexity.
Unique: Implements credential management at the MCP server layer rather than client layer, preventing LLM clients from ever handling raw Figma tokens — credentials stay within the server boundary and are injected transparently into API calls
vs alternatives: Centralizes authentication in MCP server vs distributing credentials to multiple clients, reducing attack surface and enabling credential rotation without updating all client configurations
Routes MCP tool invocations to appropriate Figma API endpoints, handles HTTP request/response cycles, and implements error recovery strategies. Translates Figma API errors into MCP-compatible error responses with context, enabling agents to understand failures and retry intelligently.
Unique: Implements MCP-aware error handling that translates Figma API errors into MCP error format, preserving error context while conforming to MCP protocol — agents receive structured error information they can reason about
vs alternatives: Provides server-side error handling and retry logic vs client-side handling, reducing complexity for LLM clients and enabling consistent error strategies across all Figma operations
Enables agents to query Figma documents with filtering capabilities, searching for specific layers, components, or design elements by name, type, or properties. Implements query translation to Figma API calls, supporting hierarchical traversal of document structure and component library lookups.
Unique: Implements query-based layer discovery that maps agent search intents to Figma API traversal, abstracting the complexity of recursive document structure navigation — agents query by intent rather than navigating API hierarchies
vs alternatives: Provides semantic search-like interface to Figma documents vs raw API access, enabling agents to express design queries naturally without understanding Figma's hierarchical data model
Extracts component definitions, design tokens (colors, typography, spacing), and style information from Figma files into structured formats. Parses Figma component metadata and applies design system conventions to normalize token names and values for downstream consumption by code generators or design tools.
Unique: Implements structured extraction of Figma design tokens and components into normalized formats, applying design system conventions to translate Figma's visual representation into machine-readable token definitions — bridges design and code domains
vs alternatives: Provides design-system-aware extraction vs generic API data fetching, enabling downstream tools to consume tokens directly without manual parsing or normalization
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 @iflow-mcp/figma-mcp at 20/100.
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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