"MCP server for accessing online documentation of open-source libraries in coding agents" matching MCP servers:

Enables AI assistants to read and create geometry in an open Cadwork 3D document via a local bridge, with queued sequential execution, write approvals, undo support, and a live dashboard for monitoring activity.

Gives LLM agents spatial awareness inside Autodesk Maya, enabling scene inspection and measurement, aesthetic and engineering audits, camera planning, checkpoint/rollback safety, asset import, and viewport or render previews. Agents can also execute arbitrary Python in Maya to build and verify 3D scenes against engineering rules instead of writing blind.

Enables AI-driven 3D modeling and scene creation in Blender, allowing LLMs to create, modify, and manipulate objects, materials, and assets through natural language.

Enables Large Language Models to access and manipulate Autodesk Revit models through a pyRevit-based bridge and the Model Context Protocol.

Connects MCP-compatible AI assistants to Azgaar's Fantasy Map Generator so they can view, inspect, edit, and export fantasy maps in a live local browser, including borders, states, terrain, layers, and files. It runs locally and offline after installation, supports collaborative manual editing, undo, autosave, and text-only map output for models that cannot see images.

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 control a live Blender session through MCP tools for scene, object, material, render, and PolyHaven asset operations. It also exposes prompt and provider tools that connect to any OpenAI-compatible, Ollama, LM Studio, llama.cpp, or Azure LLM backend, switchable at runtime.

Enables natural language control of Blender 3D through local AI models, allowing MCP clients to create, modify, and render scenes, apply materials, and execute Python code in Blender.

Enables AI agents to control a live Blender session through MCP tools for scene and object manipulation, rendering, and PolyHaven asset downloads. It works with any OpenAI-compatible, Ollama, LM Studio, llama.cpp, or Azure LLM backend, which can be switched at runtime without restarting.

Enables AI agents to control a live Blender session through scene, object, rendering, and PolyHaven asset tools while sending prompts to a provider-agnostic LLM backend that can be switched at runtime.

Lets AI agents drive a live Blender session — reading scene and object data, creating, modifying and deleting objects, setting materials, rendering images, executing code, and downloading PolyHaven assets. Prompts flow through a swappable, provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, Azure) that can be reconfigured at runtime without restarting.

Enables AI agents to control a live Blender session for scene and object management, material and render operations, and PolyHaven asset access. It also supports runtime switching between provider-agnostic LLM backends such as Ollama, LM Studio, llama.cpp, and OpenAI-compatible endpoints.

Enables AI agents to control a live Blender session over the Model Context Protocol, creating, modifying, and inspecting scene objects, applying materials, rendering images, and pulling PolyHaven assets. Prompts can be routed through a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, or Azure) that is configurable at startup or swappable at runtime.

Enables AI agents to control a live Blender session over MCP, creating and modifying objects, applying materials, rendering images, and downloading PolyHaven assets. It also routes prompts to a provider-agnostic LLM backend (Ollama, LM Studio, llama.cpp, OpenAI-compatible, Azure) that can be listed and switched at runtime.

Enables AI agents to control a live Blender session, including scene and object operations, rendering, and PolyHaven asset workflows. Supports provider-agnostic LLM backends that can be switched at runtime through MCP tools.

Enables AI agents to control a live Blender session through MCP tools for scene and object manipulation, rendering, PolyHaven asset search/download/texturing, and guided scene workflows, while allowing runtime switching between local or OpenAI-compatible LLM providers.

Enables AI agents to control a live Blender session, manage scenes, objects, materials, and renders, download PolyHaven assets, and switch between multiple LLM backends 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 through MCP tools for scene and object operations, rendering, PolyHaven asset handling, and LLM prompting. Supports multiple configurable and runtime-switchable provider backends, including Ollama, LM Studio, llama.cpp, OpenAI-compatible endpoints, and Azure.

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.