| Ecosystem | 1 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Capabilities | 12 decomposed | 9 decomposed |
| Times Matched | 0 | 0 |
Create Figma design elements (text, shapes, components, images) programmatically through MCP protocol by translating natural language or structured commands into Figma API calls. The system maps high-level design intent to Figma's object model, handling layer creation, property assignment, and parent-child relationships in the design hierarchy.
Unique: Operates as an MCP server, enabling bidirectional design automation through Claude or other MCP-compatible clients without requiring custom Figma plugins or browser extensions. Abstracts Figma's REST API into conversational design commands.
vs alternatives: Integrates directly into LLM workflows via MCP protocol, enabling design generation as part of multi-step AI reasoning chains, whereas Figma plugins require manual UI interaction or separate API orchestration.
Apply visual styling (colors, typography, spacing, effects) to multiple design elements simultaneously through batch operations. The capability translates style specifications into Figma's property model, applying fills, strokes, typography settings, and layout properties across selected or filtered element sets in a single coordinated operation.
Unique: Implements batch styling through MCP protocol, allowing style application to be triggered from LLM reasoning chains with natural language specifications like 'apply primary brand color to all buttons' rather than manual Figma UI interaction.
vs alternatives: Enables programmatic design token application at scale through conversational interfaces, whereas Figma's native batch operations require manual UI selection and Figma plugins require custom development per use case.
Manage Figma design file metadata, versions, and organizational properties through MCP protocol. The capability enables file creation, renaming, version tracking, and property management, supporting design file lifecycle operations and version control integration.
Unique: Provides programmatic file and version management through MCP protocol, enabling design file lifecycle operations integrated into development workflows and CI/CD pipelines.
vs alternatives: Automates design file management through LLM-driven workflows, whereas Figma's UI requires manual file operations and existing design tools typically don't integrate version management with development workflows.
Manages colors and fills for design elements, supporting solid colors, gradients, and image fills. Binds colors to Figma color variables, enabling dynamic theming and bulk color updates. Supports color palette management, enabling creation and organization of color systems. Implements color extraction and analysis for understanding design color usage. Coordinates with design system variables to maintain color consistency across designs.
Unique: Integrates color management with Figma's variable system, enabling dynamic theming and bulk color updates through variable changes. Supports color palette management and extraction for design system documentation.
vs alternatives: More maintainable than static color application because variable-bound colors update automatically when variables change; enables design-to-code pipelines where colors are extracted as design tokens for CSS generation.
Configure and apply auto layout properties to design frames, enabling responsive component behavior through MCP commands. The system translates layout specifications (direction, spacing, alignment, sizing) into Figma's auto layout model, automatically arranging child elements and maintaining responsive behavior across different viewport sizes.
Unique: Exposes Figma's auto layout engine through MCP protocol, enabling responsive layout configuration via natural language commands like 'create a horizontal stack with 16px spacing' without requiring Figma UI interaction.
vs alternatives: Integrates layout automation into LLM workflows, allowing responsive design generation as part of multi-step design reasoning, whereas Figma's UI requires manual configuration and design-to-code tools often lose layout semantics in translation.
Create, update, and organize Figma components and design variables programmatically through MCP protocol. The capability manages component definitions, instances, overrides, and design variable bindings, enabling systematic component library construction and design token management without manual Figma UI interaction.
Unique: Manages Figma's component and variable systems through MCP protocol, enabling design system construction via conversational commands like 'create a button component with color and size variables' integrated into LLM workflows.
vs alternatives: Automates component library creation through natural language specifications in LLM contexts, whereas Figma's UI requires manual component creation and existing design system tools typically operate outside Figma's native component model.
Export design assets (images, SVGs, PDFs) and generate HTML/CSS code from Figma designs through MCP commands. The system translates Figma design properties into web-standard formats, extracting visual properties, layout specifications, and component structures into exportable code and assets.
Unique: Generates HTML/CSS directly from Figma designs through MCP protocol, enabling design-to-code workflows within LLM contexts where the AI can reason about design properties and generate corresponding code in a single interaction.
vs alternatives: Integrates design-to-code generation into LLM reasoning chains, allowing AI to generate both designs and implementation code, whereas traditional design-to-code tools are separate applications requiring manual handoff between design and development.
Manage Figma pages, frames, and element selections programmatically through MCP protocol. The capability enables navigation, creation, and manipulation of page hierarchies, frame organization, and element selection for targeted operations on specific design areas.
Unique: Provides programmatic page and selection management through MCP protocol, enabling design file organization and element targeting via natural language commands like 'select all buttons on the components page' within LLM workflows.
vs alternatives: Automates design file organization through conversational interfaces integrated into LLM contexts, whereas Figma's UI requires manual navigation and existing automation tools typically operate outside the design file structure.
+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 Conduit for Figma at 34/100.
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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