"A tool for finding relevant academic publications and open-source projects on GitHub" matching MCP servers:

A multi-step academic figure agent harness that enables AI agents to plan, generate, evaluate, and iterate publication-grade figures from sources like PMIDs, preprints, or freeform briefs.

Enables an AI assistant to batch-drive ArmorPaint headlessly via its native CLI and scripting engine, re-exporting projects at different presets and building procedural materials without opening the GUI.

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.

Enables agents to commission and refine web pages, product prototypes, landing pages, decks, images, and motion through the desktop app, and to read design files, copy artifacts, and access design systems.

Enables assistants to publish readable replies and status updates to e-ink displays and Home Assistant, with switchable characters and state retrieval through MCP tools.

Enables MCP agents to generate open-weight videos through Amazon Bedrock AgentCore Gateway tools, with job polling, safety screening, provenance manifests, tenant isolation, and GPU cost reporting on scale-to-zero spot instances.

Lets an LLM see what's on your screen by capturing an entire monitor or a specific application window.

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.

Official MCP server for Theta EdgeCloud's On-Demand Model APIs, providing access to 20+ AI models including image generation, audio transcription, and LLMs, directly from MCP-compatible clients.

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 local OCR transcription of images using tesseract.js, with optional low-token AI-generated descriptions, folder batch processing, and compatibility with MCP clients like ChatGPT, Claude, opencode, and Cursor.

A streamlined MCP server for XMP metadata embedding with beautiful formatting and smart filename indicators, enabling metadata embedding, reading, validation, and report generation for lifestyle, product, and orbit schemas.

Enables MCP clients to discover OpenRouter image and video models, generate and edit images, create variations, launch and monitor video jobs, and save resulting media into authorized local project directories with cost controls.

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

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 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 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.