"A personal assistant tool for managing schedules, notes, projects, and emails" matching MCP servers:

MCP server providing weather lookup, semantic search over personal notes (RAG), and image generation tools for any MCP client like Claude Desktop.

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.

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.

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.

This MCP server analyzes product photos using AI to generate listing drafts, publishes to Mercari Shops via GraphQL API, and exports drafts for other marketplaces.

Provides vision capabilities to Reasonix, enabling analysis of images/videos, OCR, and comparisons via OpenAI-compatible vision models.

Bridges DeepSeek (text-only) with vision models via MCP, enabling image description and compression using any OpenAI-compatible visual API.

A self-hosted server that lets users prepare marketplace listings from photos in ChatGPT, review a draft, and publish only after explicit confirmation, with mock and live modes.

A customizable Model Context Protocol server implementation that enables AI models to interact with external tools including weather queries, Google search, and camera control functionality.

Enables AI assistants to programmatically inspect projects, create compositions and layers, apply effects, animate properties, and manage render jobs in Adobe After Effects through natural language.

Enables WorkBuddy and other MCP-compatible clients to generate images and videos from natural-language prompts through Agnes AI, returning online URLs and locally saved files.

A server that allows AI tools like Claude and Cursor to automate and control Photoshop through natural language commands, enabling tasks like editing PSDs, toggling layers, and generating marketing creatives.

MCP server that exposes ComfyUI image and 3D generation as a single tool with smart prompt classification. It enables AI assistants to generate assets directly by selecting and running the appropriate ComfyUI workflow.

Enables image and video processing through FFmpeg, including compression, format conversion, resizing, and batch processing operations for common media formats.

Enables LLMs to drive Blender through socket-based two-way communication, letting them create and modify 3D objects, apply materials, run Blender Python, and fetch or generate assets while visually verifying results. Supports prompt-assisted 3D modeling, scene creation, and manipulation.

MCP server for MarkItUp's AI image-annotation pipeline. Generate polished marketing-visual variations of any screenshot, regenerate, AI outpaint, and remove backgrounds — powered by Claude analysis + Gemini rendering.

Enables AI clients to drive local video editing projects through a CEP bridge, covering media ingest, sequence and timeline editing, effects, keyframes, captions, markers, audio, color, and exports across hundreds of discoverable tools. Ships context resources, guided prompts, and higher-level assembly workflows for agent-driven editing.

An MCP server for generating images and checking generation status through ComfyUI's API. It allows interaction with local ComfyUI instances by providing workflow-based image generation and status checking tools.

Enables AI agents to perceive and quantitatively verify physical hardware through USB webcams and RTSP/HTTP network streams, returning inline image content plus numerical metrics such as brightness, contrast, edge density, motion, SSIM baseline comparisons, and OCR text. Agents can watch feeds for visual conditions, correlate buffered frames with serial/log/MQTT events, and apply privacy masks and access controls.

Enables LLM clients to invoke standardized MCP tools across stdio, HTTP, and Cloudflare Workers, returning Markdown and structured results; the current scaffold includes an echo tool, with GPT Image generation and editing tools planned.

Enables AI assistants to control a Blender instance through MCP tools, supporting scene creation, editing, and asset exchange via HTTP and background CLI processes.

Provides tools to fetch IIIF manifests and retrieve specific image regions or scaled images for analysis. This server enables detailed interaction with International Image Interoperability Framework resources, supporting tasks like image description and transcription.

Enables interaction with Figma designs through the Figma API, allowing users to export images in multiple formats, extract style data and CSS, analyze design elements, and retrieve SVG code from Figma files. Supports batch operations and comprehensive design element analysis including images, vectors, and components.

Enables LLM clients to access crop yield predictions from RGB imagery, topic-based PDF literature, and soil lab/moisture CSV data.

Renders validated declarative scene specifications into MP4 videos inside disposable, network-disabled containers, then serves an embedded player with playback controls and diagnostics through MCP Apps. Users can iteratively revise scenes conversationally, with revision history preserved and identical renders reused per account.

Enables AI assistants to create Material Maker node graphs from natural language, validate them against the node catalog, and render them headlessly to PBR texture maps and editable .ptex files.