"Scheduler that invokes the agent based on a predefined schedule" matching MCP servers:

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.

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.

Hosted MCP server (OAuth, no API keys) that makes short drama series (micro-dramas, sitcoms, K-drama style, any language) and other short vertical videos from Claude, ChatGPT or Codex, with the same cast every episode.

Give text-only LLM agents eyes by describing images through a vision-language model via MCP or CLI.

A lightweight MCP server that enables text agents to analyze images and videos using OpenAI-compatible vision models, with tools for image analysis and video frame extraction.

Provides a catalog of paid micro-work tools for text processing, speech, and image generation with fixed USDC pricing via x402. Enables agents to discover capabilities, get quotes, and prepare calls without handling wallet keys.

A local stdio MCP server for visual AI work, offering an Excalidraw infinite canvas, image generation and editing, HTML drafts, presentations, and durable task recovery within a project workspace.

Provides local vision and audio perception for MCP-compatible agents, enabling them to read images, transcribe text from visual media, analyze videos, and convert speech to text entirely on-device. It is privacy-focused with no cloud upload or API keys by default, using Ollama for inference.

TCG oracle as an MCP server: 22 focused tools. Search 455K+ trading cards, live market snapshots, AI grading and grade-or-not decisions, conformal-calibrated price forecasts with a public accuracy scorecard, card-collateral loan terms, fantasy and sports souls leagues. Every root proven on-chain. Same tools as the hosted endpoint at mcp.the-undesirables.com, over stdio; no keys.

Enables local-first creation, editing, and animation of pixel-art Aseprite documents through MCP stdio, with atomic previews, canvas drawing, layers, frames, palettes, tags, slices, tilemaps, and cast tools. It also supports strict asset validation and verified Phaser/game-asset export from reopened native masters.

Enables AI agents to find meme and reaction clips via the Vlipsy API or local folders, look at them as contact-sheet images, and fetch or convert them into rendered assets with attribution sidecars. It also drops those clips into ffmpeg renders and editing timelines (OTIO, FCPXML, Premiere XML, EDL) or returns paste-ready Remotion, HyperFrames, MoviePy and HTML snippets.

Enables AI agents to drive a live Blender session over stdio, inspecting the scene graph, searching and calling operators, reading and writing RNA properties, rendering viewable images, and checkpointing or restoring the file across a multi-turn conversation. It also exposes gallery and scene-reset helpers so the agent can check its own work and start over cleanly.

An MCP server that enables AI clients to inspect footage and audio, edit revision-locked timelines or generated source code, render with Remotion or HyperFrames, and verify results through measurements for iterative video editing.

Enables applications and AI agents to inspect, convert, extract, and process media through asynchronous HTTP and MCP tasks, with optional natural-language planning and A2A interoperability.

MCP server for generating print-ready 3D models from text descriptions via a multi-agent pipeline, enabling AI assistants to create and optimize STL files.

Enables AI agents to inspect and control a running WARUDO scene, including assets, character pose and IK, expressions, blueprints, camera, and captures, through an MCP client.

Enables MCP clients to generate images from text prompts and edit existing PNG/JPEG files with natural-language instructions by driving a local ComfyUI instance running Qwen Image models. Supports aspect ratios, exact pixel dimensions, batch counts, and reproducible seeds, with matching capabilities exposed through a Python CLI.

Provides image analysis, inspection, cropping, OCR, and comparison capabilities via the Model Context Protocol, allowing AI agents to process and manipulate images using vision models.

Enables users to classify steel surface defect images and retrieve aggregate model performance metrics through MCP tools, while supporting confidence-based human review and drift monitoring in an agent pipeline.

This MCP server enables image generation via Codex CLI and an OpenAI-compatible relay API, with job queue, status polling, and preview/download endpoints. It is a single-user local demo without authentication or persistence.