AIttache: A Read-Only MCP Server That Can't Nuke Your Prod
The author of AIttache calls it the antidote to MCP servers that will "happily let your LLM rm -rf something important while you're making coffee." Instead of agentic autonomy, AIttache is physically incapable of doing anything beyond requesting info from the connectors you provide. It's a read-only bridge.
Key Design Decisions
- 25+ read-only connectors: your terminal, your servers, the weather, your Steam library — the LLM gets to look, not touch.
- Zero write operations: no
rm, no config changes, no executing commands that mutate state. The server refuses anything that isn't a GET-style request. - Context, not autonomy: the useful part of having an LLM in infrastructure work is the context. This spares you from copy-pasting 300 lines of logs into a chat window.
Philosophy
The creator explicitly positions AIttache as a "sparring partner with situational awareness, not a chatbot that nukes prod at 8AM on a Monday because it was pretty sure it knew what it was doing." The core argument: "what could possibly go wrong" is not a viable deployment strategy.
Who It's For
Developers who want LLM-assisted troubleshooting (log analysis, error context, system inspection) without granting write access to their infrastructure.
📖 Read the full source: r/ClaudeAI
👀 See Also

Skillware adds prompt_rewriter for deterministic token compression in Claude API agent loops
Skillware has merged a new prompt_rewriter skill that compresses prompts by 50-80% before sending to Claude API, reducing costs in agentic loops while maintaining stable behavior through deterministic compression.

Dynamic Status Bar for Claude Code Shows Live Updates
A developer has improved their Claude Code status bar from static text to dynamic display with real-time updates showing what Claude is working on. The configuration is available as a GitHub gist.

Building a Local Open-Source AI Workspace with Rust and Tauri
Explore a fully local, open-source AI workspace built using Rust, Tauri, and sqlite-vec, without a Python backend.

GuppyLM: A 9M Parameter LLM Built from Scratch for Educational Purposes
GuppyLM is a ~9M parameter language model trained from scratch on 60K synthetic conversations, using a vanilla transformer architecture with 6 layers, 384 hidden dimensions, and 6 attention heads. It trains in about 5 minutes on a free Colab T4 GPU and speaks with a fish personality focused on water, food, and tank life.