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RoboFang — Multi-Agent Coordination Hub

RoboFang is an orchestration layer for local AI agents, designed to bridge a federated fleet of MCP servers with physical robotics and virtual environments.


Documentation

Standard technical documentation is organized by category:

Domain Description
Architecture Multi-process topology and module layout.
Setup Local deployment guide (UV, Ollama, Dashboard).
Council Protocol Multi-model coordination and adjudication logic.
Fleet Management Port registry and connector integration for the 30+ server fleet.
Autonomous Hands Manifest-driven background processes.
Comparison Matrix Technical mapping against OpenClaw and OpenFang.
Roadmap Strategic development phases and priorities.
Status Operational health and tech debt registry.

Technical Overview

Deployment Stack

  • Backend: FastAPI + FastMCP 3.1+ (Python 3.12).
  • Frontend: React + Vite (Port 10864).
  • Adjudication: Council of Dozens (Foreman/Worker/Satisficer logic).
  • Inference: Local Ollama (Primary).

Core Features

  • Local-First: Zero-token cost operations via optimized local models.
  • Unified Tool Surface: Standardized API gateway for heterogeneous MCP backends.
  • Embodiment: Joint control for robotics (Bumi, Yahboom) and VR systems (Resonite, VRChat).
  • Security Gates: Policy-driven adversarial adjudication for sensitive operations.

Quick Setup

  1. Environment: uv sync
  2. Backend: uv run python -m robofang.cli start bridge
  3. Frontend: cd dashboard; .\start.ps1

Visit http://localhost:10864 to manage the coordination node.

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openclaw / openfang inspired experiment. adds mcp server fleet and robotics

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