"Actual Budget" matching MCP servers:

Local MCP server that plans, generates, and assembles production assets (images, audio, video) through multi-agent personas and official APIs, with free-tier budget guard.

MCP server for Blender that connects to the official Blender Lab add-on, exposing 27 tools for scene manipulation, object editing, materials, rendering, and Python execution through the add-on's actual wire protocol.

An agentic AI video editor for Claude. It enables editing real video through MCP: cutting, captioning, reframing, scoring, and exporting finished MP4s from actual footage.

Enables coding agents to watch and analyze videos by extracting scene-aware frames, transcribing speech, and generating shot timelines, all constrained by a token budget to fit LLM context limits.

Enables AI agents to drive a desktop video editor through MCP, providing the same editing operations as the user — placing, trimming, rippling, grading, captioning, and exporting — on the actual project with local rendering.

Enables AI models to decode QR codes from images by providing tools that scan and enhance QR codes, returning content and image quality diagnostics. It bridges the gap between visual recognition and actual decoding, allowing models to read QR codes directly from screenshots or photos.

Enables AI agents to browse video production packages, obtain free quotes, start and track productions with budget safeguards, and download finished videos, thumbnails and subtitles from vidia.kr. It also supports account balance checks and asset library lookups through MCP clients such as Claude, Cursor and Codex.

Enables any MCP client to turn layered PSD artwork into game-ready Spine packages by inspecting and classifying layers, rigging with meshes, bones, weights, IK, physics and animation, applying procedural or After Effects-driven FX, and running runtime and mobile-budget validation with preview output. It finishes by exporting the final .spine, JSON and atlas assets so a model can drive a full art pipeline without hand-authoring rig data.

Enables AI clients to turn text prompts and 2D photos into watertight 3D-printable figurines, keyed multi-part assemblies, and game-ready PBR assets entirely on local consumer hardware within a 16 GB RAM/VRAM budget. It exposes 16 native tools covering image-to-3D generation, pose canonicalization, auto-split assembly, retopology, texture baking, and hardware tier detection over stdio.