Building a Jarvis-Style AI with MCP and Open Models
A developer on r/LocalLLaMA shared a Jarvis-style AI assistant built using the Model Context Protocol (MCP) and open models. The system is still work in progress but already supports several agentic features.
Key Details
- Memory — persistent context across sessions
- Autonomous file editing — the AI can read and write files on its own
- Visible tool-call tracing — users can see each step the AI takes
- Confirmation before dangerous actions — safety guardrails for destructive operations
- Persistent context — maintains state over time
- Hybrid local/cloud inference — can switch between local and cloud models
The primary model is Qwen3-Coder 480B running in the cloud for reasoning and tool usage, because smaller local models hallucinate too much with MCP workflows. The user is now working on Windows UI automation, dynamic skills, and AI-generated skill creation so the assistant can expand its own capabilities. The goal is a practical AI operator that interacts with and automates the user's computer, not just another chatbot.
Who It's For
Developers experimenting with local AI agents, MCP-based tool use, and autonomous computer automation using open-weight models.
📖 Read the full source: r/LocalLLaMA
👀 See Also

Claude IDE Bridge: WebSocket Tool for Real-Time IDE Access
claude-ide-bridge is a WebSocket bridge that connects Claude Code directly to IDE internal state, enabling live diagnostics, go-to-definition, find references, type hovering, file opening, breakpoint management, and debugger state streaming.

Claude Code Skill Delegates Coding to Mistral/DeepSeek: 57M Tokens Saved, 90-100% Cost Reduction
A Claude Code skill called vibe-skill delegates low-level coding to cheap models like Mistral or DeepSeek while keeping Claude's planning. After 254 runs over 10 days, it saved 57M tokens and achieved 90-100% cost savings with 98% success rate.

V6rge AI Suite Update Adds NVIDIA GPU Support and Beta Coding Agent
V6rge AI Suite has released an update that fixes GPU detection issues, adds full NVIDIA GPU support for better performance, and introduces a new beta coding agent that generates and assists with code directly inside the app.

TOON MCP server reduces tool result tokens by 30-60% in OpenClaw
An MCP server that compresses structured JSON tool results into the TOON format can cut token usage by 30-60% for tabular data like database queries and API responses, helping delay context window compaction in OpenClaw sessions.