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Documentation Index

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Welcome to ApexSpriteAI — a sophisticated AI agent orchestration platform that puts the power of large language models directly in your hands. Whether you’re running local models on dedicated GPU hardware or integrating cloud AI into your workflows, ApexSpriteAI provides the tools you need to build fast, capable, and extensible AI coding assistants.

Quick Start

Get your AI agent running in minutes with step-by-step setup instructions.

Architecture Overview

Understand how ApexSpriteAI’s components fit together.

MCP Tools

Extend your AI agent with the Model Context Protocol tool system.

Model Selection

Choose the right model for your speed and capability requirements.

Get up and running

1

Set up your local AI backend

Install LM Studio and load your preferred model on your GPU hardware. ApexSpriteAI supports models from 16B to 120B parameters.
2

Configure your network

Connect your local Mac or workstation to your GPU server securely over Tailscale VPN, or run everything on a single machine.
3

Connect Claude Code CLI

Point the Claude Code CLI at your local LM Studio backend to get an AI-powered coding assistant with full MCP tool support.
4

Add MCP tools

Extend your agent’s capabilities by installing MCP tools for file access, web search, code execution, and more.

Why ApexSpriteAI?

Local & Private

Run AI models entirely on your own hardware. No data leaves your network.

GPU Accelerated

Leverage NVIDIA GPU hardware for fast, low-latency inference even with large models.

Extensible via MCP

The Model Context Protocol lets your AI agent use tools like file read/write, shell commands, and custom integrations.

Open Model Ecosystem

Works with Qwen2.5-Coder, Llama 3.3, DeepSeek, and any model compatible with LM Studio.