"PostHog: Open-source product analytics platform" matching MCP servers:

Enables local Blender-based product modeling and photography by exposing project management, scene editing, rendering, image inspection, and asset publishing tools to MCP hosts like Claude Code, with versioned .blend revisions and PNG renders.

Enables AI agents to remotely operate visual design tools via MCP protocol, with composable architecture for image processing, file operations, and workflow automation.

Enables AI agents to drive a user's own signed-in Google NotebookLM (Gemini Notebook) account through 51 MCP tools, covering notebook and source management, grounded chat with numbered citations, fast and deep research, and generating or downloading audio/video overviews, slide decks, quizzes, flashcards, mind maps, infographics, reports and data tables. It runs over stdio or streamable HTTP on localhost and sends progress notifications for long-running jobs.

Enables small models to turn a short brief into complete HTML pages or looping GIFs with typography, palette, borders, motion, and validation already decided. It also lets agents list styles, retrieve style rules, create assets, validate HTML, and access reference examples.

Enables AI agents to generate images, videos, and lip-sync media, and to query wallet balances via the Open Generative Studio instance.

Provider-neutral Vision MCP Server — image analysis via 10 inference providers through a single MCP server.

Enables AI coding agents to perform end-to-end medical image analysis locally, from inspecting CT/MRI/X-ray studies and running containerized segmentation models like MedSAM2, TotalSegmentator, and HD-BET to refining masks, measuring volumes, and writing reports. It pairs preset or custom guideline protocols with a code-customizable viewer that renders images back to agents as annotated PNGs and to humans as interactive HTML.

Exposes Open Video Guide functions to MCP clients, enabling conversion of tutorial videos into illustrated, verifiable guides with timestamps, evidence, and review states.

A server that integrates Blender with local AI models via the Model Context Protocol, allowing users to control Blender using natural language prompts for 3D modeling tasks.

Enables recognition and extraction of architectural CAD drawings (DWG) by creating tasks and retrieving structured results for frames, title blocks, and 23 building component types, including rooms, doors, windows, stairs, and text.

Enables AI agents to control a live Blender session, including scene and object operations, materials, rendering, PolyHaven asset downloads, and prompts to configurable LLM backends through MCP tools.

Enables AI agents to control a live Blender session for scene/object manipulation, rendering, code execution, and PolyHaven asset/texture management. It also supports runtime switching among Ollama, LM Studio, llama.cpp, OpenAI-compatible, and Azure backends.

Enables AI agents to control a live Blender session and use configurable LLM backends through MCP tools for scene/object editing, rendering, asset search/download, and runtime provider switching.

Enables AI agents to drive a live Blender session over MCP by inspecting scenes, creating and modifying objects, assigning materials, rendering images, and fetching PolyHaven assets. It also exposes prompt-based scene building and review workflows backed by a provider-agnostic LLM layer (Ollama, LM Studio, llama.cpp, OpenAI-compatible endpoints, Azure) that can be switched at runtime.

Enables AI agents to control a live Blender session for scene and object creation, modification, rendering, and PolyHaven asset workflows, while routing prompts through configurable local or remote LLM backends that can be switched at runtime.

Enables AI agents to control a live Blender session, manage scene objects and materials, render images, fetch PolyHaven assets, and send prompts to configurable local or OpenAI-compatible LLM providers with runtime switching.

Enables AI agents to control a live Blender session through the Model Context Protocol, exposing tools for scene and object management, materials, rendering, and PolyHaven asset downloads. It also lets agents send prompts to a swappable LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, or Azure) and switch providers at runtime.

Enables AI agents to inspect and modify live Blender scenes, manage objects and materials, render images, retrieve PolyHaven assets, and send prompts to configurable local or OpenAI-compatible LLM backends.

Enables AI agents to control a live Blender session through MCP tools for scene/object manipulation, rendering, PolyHaven asset access, and guided scene-building prompts. It supports provider-agnostic LLM backends that can be configured or switched at runtime.

Enables AI agents to control a live Blender session through the Model Context Protocol, including scene and object operations, rendering, PolyHaven asset integration, and prompt-driven workflows. It supports multiple local or OpenAI-compatible LLM backends that can be switched at runtime.