"GPT-SoVITS MCP (Model Context Protocol) Integration" matching MCP servers:

Enables converting layered PSD or PhotoshopToSpine exports into validated Spine 2D rigs, animations, atlases, previews, runtime JSON, and optionally editable .spine projects. It provides MCP tools and an OpenAI/Codex workflow for rigging, animation generation, validation, preview auditing, and batch processing.

Enables an AI assistant to open 3D model files (STL, 3MF, Bambu Studio and OrcaSlicer projects) in a local browser viewer where the user clicks exact spots to leave feedback. Each note comes back with the part name, millimetre coordinates, surface direction and a numbered screenshot, so the assistant can revise the design and show the new version.

Ask, check and change live Revit models from Claude, Cursor or any MCP client. One undo per change, read-only switch. Revit 2022-2027.

A Model Context Protocol (MCP) server that enhances Figma design integration by adding element position information to API responses, enabling AI assistants to better understand spatial relationships and convert designs to code more accurately.

Converts Lanhu design URLs into AI-ready implementation context including HTML+CSS (Tailwind), image downloads, design tokens, and guidance.

Open, secure runtime that puts Revit, Rhino, Navisworks, and Power BI behind one MCP call center, enabling an AI agent to orchestrate them directly instead of manually dumping data between disconnected apps.

Loads your project's Tailwind CSS config and exposes tools for AI agents to query actual design tokens and validate class names, preventing hallucination of non-existent utilities.

A read-only MCP server that extracts actual Figma prototype flows, transitions, and per-screen interactions so agents can see navigational behavior rather than infer it. It reports explicit source and destination IDs with warnings for unresolved or ambiguous destinations, without guessing or writing back to Figma.

Converts Figma designs into structured code context with token-aware styling, enabling AI agents to generate production-level frontend code.

Enables users to generate rigged, game-ready gun models in Blender from parameterized presets or platforms, including attachments, animation clips, fact sheets, and reference-photo validation.

Integrates PTC Windchill and Creo Parametric with LLM-based clients via the Model Context Protocol, enabling natural language interaction with PLM and CAD systems for tasks like part search, BOM retrieval, model operations, and exports.

An MCP server that gives AI coding tools access to Figma design data for accurate one-shot implementation of designs.

An MCP server that gives AI coding agents access to Figma design data, enabling pixel-perfect implementation of designs through structured data extraction, image downloads, and design token retrieval.

Exposes tools to ingest FigJam boards, retrieve context summaries, and answer free-form questions about the board content.

Applies Jungian shadow complement to unified composition parameters, creating psychological depth through systematic visual opposition after multi-domain blending.

Converts Figma design data into structured semantic analysis JSON and screenshots for AI agents to use in design-to-code workflows.

Enables AI agents to extract design systems, analyze components, and maintain design-code consistency from Figma files, providing intelligent component analysis and accessibility compliance.

Enables coding agents like Cursor to access Figma design data, fetch layout and styling information, and implement designs in any framework.

Enables Cursor to access Figma design data via MCP, allowing it to fetch simplified layout and styling information to accurately implement designs from Figma files.

Enables AI clients to control a running Blender instance through the Model Context Protocol, allowing scene inspection, object creation and editing, rendering, and execution of Blender Python. It works locally via a WebSocket bridge between the MCP server and a Blender add-on.