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Claude Code Is Built Entirely on MCP - What the Source Leak Revealed

Claude Code Is Built Entirely on MCP - What the Source Leak Revealed

Claude Code doesn’t use MCP as a plugin system. It is MCP. On March 31, 2026, Anthropic shipped a 59.8 MB source map by accident in npm package @anthropic-ai/claude-code v2.1.88. Developers got a rare look at how a real AI coding agent works. Every capability in Claude Code (file reads, bash, web fetches, Computer Use, IDE bridges) runs as a single permission-gated MCP tool call. There is no special internal API. Third-party MCP servers you connect get the same execution path, permission checks, and error handling as Anthropic’s own built-in tools.

The Claude Code Source Leak: What 512,000 Lines of TypeScript Revealed About AI Agent Architecture

The Claude Code Source Leak: What 512,000 Lines of TypeScript Revealed About AI Agent Architecture

One missing line in a build config caused the worst source leak in AI tooling history. On March 31, 2026, Anthropic shipped version 2.1.88 of its @anthropic-ai/claude-code package with a 59.8 MB JavaScript source map inside. That map held the full client agent harness for Claude Code : 512,000 lines of readable TypeScript in 1,906 files. Mirrors of the code spread thousands of times in hours. A clean-room Python/Rust rewrite then became the fastest-growing repo in GitHub history. Anthropic’s legal response hit the wrong targets. The day got worse: a supply-chain attack hit the axios npm package, piling on for devs who rely on these tools.

Build a Portable Hacking Lab with a Raspberry Pi 5

Build a Portable Hacking Lab with a Raspberry Pi 5

You can build a self-contained pen testing lab on a Raspberry Pi 5 running Kali Linux ARM64. Add a battery HAT, a 7-inch display, and a wireless adapter that does packet injection. Total cost lands between $200 and $250. The result is a pocket-sized hacking kit that runs Nmap, Burp Suite, Wireshark, Aircrack-ng, and Metasploit in the field, at CTF events, or on jobs where you can’t lug a laptop.

Local AI Security Cameras: Frigate with Google Coral TPU

Local AI Security Cameras: Frigate with Google Coral TPU

Cloud security camera fees have quietly become one of the priciest bills in the smart home. At $10 to $30 per camera each month, a full setup runs $500 to $1,000 a year. You pay that to have your own footage handled on someone else’s servers. Frigate NVR changes the math. Paired with a Google Coral TPU , it runs real-time AI person and object detection across many 4K streams. Inference times stay in the single-digit milliseconds. It all runs on hardware you own, on a network that never phones home.

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Gemma 4 vs Qwen 3.5 vs Llama 4: Which Open Model Should You Actually Use? (2026)

Gemma 4 vs Qwen 3.5 vs Llama 4: Which Open Model Should You Actually Use? (2026)

Gemma 4, Qwen 3.5, and Llama 4 compared on benchmarks, licensing, speed, and hardware so you can pick the right open model fast.

5 Open Source Repos That Make Claude Code Unstoppable

5 Open Source Repos That Make Claude Code Unstoppable

Five March 2026 repos extend Claude Code with autonomous ML, self-healing skills, GUI automation, multi-agent coordination, and Google Workspace access.

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DeepSeek V4 Tech Report: 3 Tricks That Cut Compute 73%

DeepSeek V4 ships 1.6T parameters and 1M context using only 27% of V3.2's inference FLOPs. Inside the hybrid attention, mHC residuals, and Muon optimizer.

Cracked stone tablet engraved with a bulleted system prompt, four crossed-out goblin silhouettes repeated, a tiny goblin escaping with upvote-arrow sparks, a giant dollar-sign price tag, and figures refusing to step onto a glossier pedestal.

GPT 5.5 Reddit Reception: Goblins and the Cost Backlash

GPT-5.5 Reddit reception: viral goblin prompt leak, doubled pricing backlash, and 5.4 holdouts citing hallucination regressions in factual recall workflows.

What X and Reddit Users Are Saying about Claude Opus 4.7

What X and Reddit Users Are Saying about Claude Opus 4.7

How power users on X and Reddit reacted to Claude Opus 4.7: praise for agentic coding, token burn concerns, and teams' practical prompting habits.

Qwen3.6-35B-A3B: Alibaba's Open-Weight Coding MoE

Qwen3.6-35B-A3B: Alibaba's Open-Weight Coding MoE

Alibaba's sparse Mixture-of-Experts: 35B total parameters, 3B active per token. Q4 quantization runs on MacBook Pro M5, matches Claude Sonnet performance.

Alacritty vs. Kitty: Best High-Performance Linux Terminal

Alacritty vs. Kitty: Best High-Performance Linux Terminal

Alacritty vs Kitty in 2026: emoji and Unicode rendering, real benchmarks, latency, memory, maintainer reputation, and the right terminal for your workflow.

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