MediaClaw: Multimodal Intelligent-Agent Platform Technical Report

TL;DR

MediaClaw is a multimodal agent platform designed to unify, extend, and orchestrate AI capabilities, addressing deployment challenges in AI-generated content through a modular, workflow-based architecture.

Contribution

It introduces a three-layer architecture with unified abstraction, plugin support, and workflow orchestration for practical multimodal AI deployment.

Findings

Abstracts full-category AIGC capabilities into a unified model

Supports hot-pluggable capability expansion via plugins

Turns complex production processes into reusable workflows

Abstract

MediaClaw is a multimodal agent platform built on the OpenClaw ecosystem. Its core design follows a three-layer architecture of unified abstraction, pluginized extension, and workflow orchestration. The system is intended to address practical deployment pain points in AIGC adoption, including fragmented capabilities, heterogeneous interfaces, disconnected production processes, and limited reuse of high-quality production workflows. \system{} abstracts full-category AIGC capabilities into a unified invocation model, uses plugins to support hot-pluggable capability expansion, and uses task-oriented Skills to turn complex production processes into reusable workflow assets. This report focuses on the architectural design philosophy of MediaClaw, the design logic of its core capability model, and the key engineering trade-offs in implementation. It aims to provide reusable practical reference for building multimodal capability platforms.