About
The D-ZERO MCP Server provides an MCP interface for retrieving Figma design data and delivering coding guidelines. It integrates with CLINE’s AI assistant, enabling developers to reference designs and standards directly within conversational workflows.
Capabilities

Overview
The D‑ZERO MCP Server is a specialized Model Context Protocol (MCP) service designed to streamline front‑end development workflows for the D‑ZERO ecosystem. It bridges the gap between visual design assets and code by exposing Figma data through a simple API, while also delivering the project's coding guidelines directly to AI assistants. By integrating with CLINE’s MCP infrastructure, developers can query design specifications and style rules without leaving their conversational AI environment.
Problem Solved
Front‑end teams often juggle multiple tools: design files in Figma, style guides stored locally, and AI assistants that can help answer questions or generate snippets. Switching between these contexts slows iteration and introduces friction. The D‑ZERO MCP Server consolidates these resources into a single, AI‑friendly interface, allowing developers to retrieve up‑to‑date design tokens, component hierarchies, and coding conventions with a single request. This eliminates manual look‑ups, reduces copy‑paste errors, and keeps the team’s knowledge base consistent.
Core Functionality
- Figma Data Retrieval: The server authenticates with the Figma API using a bearer token, then exposes endpoints that return file or node metadata. Developers can request entire files, specific layers, or design tokens in JSON format, which the AI assistant can parse and incorporate into code generation or review.
- Coding Guidelines Distribution: A dedicated endpoint serves the D‑ZERO front‑end style guide. When an AI assistant asks for best practices, the server returns structured guidance that can be embedded in prompts or used to validate generated code.
- CLINE Integration: By registering itself as an MCP server in CLINE’s configuration, the service becomes discoverable by any AI assistant that supports MCP. The file configures the server’s command, environment variables, and auto‑approval settings, ensuring seamless operation within the broader CLINE ecosystem.
Use Cases & Real‑World Scenarios
- Rapid Prototyping: A developer can ask the AI assistant to “show me the color palette for the login screen” and receive a JSON list of colors directly from Figma, eliminating the need to open the design file manually.
- Code Generation with Style Consistency: When generating a component, the assistant can query the coding guidelines endpoint to enforce naming conventions, spacing rules, and accessibility checks, ensuring that the output aligns with project standards.
- Onboarding New Team Members: New hires can interact with the AI assistant to fetch both design references and coding rules in one place, accelerating their ramp‑up time without navigating multiple documentation sites.
- Continuous Integration Checks: CI pipelines can invoke the MCP server to retrieve the latest design specs and compare them against committed code, automatically flagging deviations from the agreed style guide.
Advantages & Standout Features
- Single Source of Truth: By pulling live data from Figma and serving a central style guide, the server guarantees that developers always reference the most current resources.
- AI‑First Design: The MCP interface is tailored for conversational AI, allowing natural language queries to be translated into precise API calls without additional middleware.
- Developer‑Friendly Configuration: The server requires only an environment file with the Figma access token, and integration is as simple as editing . This low barrier to entry encourages rapid adoption across teams.
- Extensibility: Although focused on Figma and D‑ZERO guidelines, the architecture can be expanded to expose other design systems or documentation sources, making it a versatile backbone for any AI‑augmented development environment.
In essence, the D‑ZERO MCP Server empowers developers to leverage AI assistants as a single point of interaction for both design references and coding standards, thereby accelerating development cycles, improving consistency, and reducing context switching.
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