RepoCatAI | Sharing GitHub Projects for AI & Robot

🐾Sharing the best AI Agent & Robotics projects
Curating useful GitHub repos for builders

Follow for cutting-edge AI
DM to share your project

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

Asimov v1: Open-Source Humanoid Robot

Build your own 1.2m-tall bipedal robot with 25 actuated degrees of freedom.

Learn more: https://t.co/ZCzuvQdJ2Z

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/B1qNTVVN6O

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[BOOKMARK THIS] WholeBodyVLA — the humanoid VLA repo mapping where whole-body robot control is going

This is less “clone and run today” and more “study the blueprint before everyone else copies it.”

· Vision-Language-Action control for humanoids
→ images + language instructions become robot movement commands
· Built for loco-manipulation, not tabletop demos
→ walking across space while using both arms
· Learns latent actions from egocentric videos without action labels
→ a path toward training from human-like first-person footage
· Decodes into dual-arm joint actions + locomotion commands
· Uses an RL policy aimed at stable whole-body coordination
→ balance, walking, reaching, and disturbance handling matter together
· Includes demos like fetching coffee, moving chairs, and long-range tasks
· Also acts as a curated reading list for humanoid VLA research

Why it matters: Humanoid robotics is moving from “stand here and pick this up” toward robots that can move through real spaces and manipulate objects on the way. WholeBodyVLA is a strong signal for indie robotics builders, AI engineers, and researchers watching the merge of video learning, language control, and full-body policies.

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/puaMapIvFU

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[BUILDER'S DREAM] Browser Harness lets an AI plug into your real Chrome and teach itself the missing moves

This is the browser-agent idea stripped down to the part builders actually want:
one thin harness, one Chrome websocket, and an agent that can edit its own tools mid-task.

· Direct CDP connection to Chrome
→ the agent talks to your actual browser, not a boxed-in automation layer
· Editable agent workspace
→ when a helper is missing, the agent writes it during execution
· Self-improving runs
→ site quirks, selectors, and flows can turn into reusable skills
· Domain skills for real websites
→ GitHub, LinkedIn, Amazon-style playbooks instead of rediscovering every click
· Tiny core architecture
→ roughly 1k lines across 4 core files, so you can actually understand it
· Works with local Chrome or cloud browsers
→ useful for stealth, headless jobs, proxies, captcha handling, and parallel runs
· Built for messy tasks like uploads, outreach, ordering, expenses, and admin work

Why it matters: Most browser agents feel impressive until they hit one weird popup, file picker, login flow, or custom UI. Browser Harness takes the opposite bet: give the agent direct browser access and a place to write the missing glue as it learns.

For indie devs and AI engineers, this is the kind of repo that can turn "AI can browse" from a demo into repeatable automation you can inspect, patch, and share.

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/7yk7SJApvf

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[INSANE] Frigate turns cheap IP cameras into a local AI security system you actually control

This is what a home NVR looks like when it is built by people who care about latency, privacy, and not melting your CPU.

· Local object detection for IP cameras
→ people, cars, pets, packages, and motion events without cloud video uploads
· Built for Home Assistant from day one
· Uses motion first, then AI only where it matters
→ less wasted compute, more real-time responsiveness
· Works with GPUs and AI accelerators
→ Coral / detector-style hardware can crush CPU-only setups
· MQTT events for automations
→ turn detections into lights, alerts, scripts, dashboards, whatever
· Object-aware recording retention
→ keep the clips that matter instead of hoarding endless footage
· 24/7 recording plus low-latency live view
· Built-in masks, zones, review flows, and multi-camera scrubbing

Why it matters: If you have cameras around a home, workshop, lab, driveway, or robot test space, Frigate gives you the missing brain. You get searchable, local, AI-assisted video infrastructure without paying a cloud vendor to watch your footage.

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/OIvMpcu1FB

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[DEEP DIVE] build-your-own-x — a giant map for recreating real tech from scratch

This is the repo you open when tutorials feel too shallow and docs feel too abstract.

· Build your own LLM, diffusion model, or RAG search system
→ learn the moving parts instead of just calling an API
· Recreate Git, Docker, a database, a shell, or a web server
· Dig into 3D renderers, ray tracers, physics engines, and voxel engines
· Follow language-specific guides in Python, Go, C++, JavaScript, Rust, Java, and more
· Learn by building the thing people usually treat as magic
· Pick projects by curiosity level, not course syllabus
· Great “weekend rabbit hole” material for engineers who want real intuition

Why it matters: Open-source AI is moving fast, but the builders who really win are the ones who understand the layers underneath. This repo gives you a practical path from “I use these tools” to “I can build a tiny version myself.”

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/GmMEmhYEqY

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[BOOKMARK THIS] Anthropic’s Knowledge Work Plugins — 11 open-source role packs for Claude

This is basically a starter kit for turning Claude from “general assistant” into “knows how this team works.”

· 11 ready-made plugins for sales, support, PM, marketing, legal, finance, data, bio research, and more
· Each plugin bundles skills, slash commands, connectors, and sub-agents
→ Claude gets role-specific workflows instead of generic advice
· File-based setup: markdown + JSON only
→ no app server, no build step, no infra project hiding inside
· Connects to real work tools like Slack, Notion, Jira, Linear, HubSpot, Figma, BigQuery, Snowflake
· Slash commands for repeatable work
→ think /sales:call-prep, /data:write-query, /finance:reconciliation
· Easy to fork for your company’s language, process, and tool stack
· Includes a plugin-management plugin for creating or customizing more plugins

Why it matters: Most “AI at work” fails because the model does not know the workflow, the tools, or the house style. This repo gives builders a clean pattern for packaging that context into something Claude can actually reuse across tasks, teams, and roles.

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/HUgKzTka1G

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[BUILDER'S DREAM] cmux — a native macOS terminal built for running AI coding agents in parallel

If your desktop is slowly turning into 12 Claude/Codex tabs and mystery notifications, this one is worth a look.

· Ghostty-based terminal, but with vertical tabs made for agent work

· Blue notification rings show exactly which pane needs you
→ no more hunting through tabs that all say “waiting for input”

· Sidebar shows branch, PR status, working directory, ports, and latest agent message

· Built-in browser panes sit beside your terminal
→ test localhost, inspect UI, and keep browser state inside the workspace

· SSH workspaces make remote machines feel local
→ browser panes route through the remote network, so localhost still works

· Claude Code Teams launches with one command
→ teammates spawn as native splits with metadata and notifications

· Reads your existing Ghostty config for fonts, themes, and colors

· Native Swift/AppKit app, not Electron
→ fast startup, lower memory, GPU-accelerated terminal rendering

Why it matters: cmux is for devs who already live in the terminal but want agent orchestration without being forced into a heavy GUI workflow. It turns “a pile of terminal panes” into a readable command center for AI coding sessions, local apps, PRs, SSH boxes, and browsers.

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/IBjZH4Je0P

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[NEW DROP] Google Antigravity SDK — Python agents with Gemini, state, tools, and streaming built in

This is the kind of repo agent builders should open before writing another custom loop from scratch.

· One async Agent class handles lifecycle, runtime discovery, tools, hooks, and policy defaults
· Starts read-only by default
→ safer for codebase agents until you explicitly enable write capabilities
· Real-time streaming responses for CLIs, dashboards, and chat UIs
· Advanced streams for thoughts and tool calls
→ show “thinking” bubbles or live “executing tool” states in your app
· Stateful Conversation API with history, turn count, last response, and step introspection
· Multimodal inputs: images, video, audio, PDFs, docs, and in-memory bytes
· Local runtime powered by a compiled binary shipped through PyPI
→ install with pip, don’t just clone the repo
· Interactive loop utility included for building quick terminal agents fast

Why it matters: Most agent prototypes get messy around the same places: state, tool execution, streaming UX, safety defaults, and runtime plumbing. Antigravity SDK wraps those pieces so you can spend more time on the actual behavior of the agent: code navigation, spec review, multimodal analysis, internal tools, or robotics-adjacent command loops.

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/LH0vTOIEaH

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[TESTED] magic-trace — see every function call before a crash or slowdown, at ~40ns resolution

This is the debugger you want when “it was slow once in prod” is all you have.

· Attach to a running Linux process like perf
· Captures every function call, not just sampled stack snapshots
→ you can inspect the tiny calls normal profilers miss
· Uses Intel Processor Trace under the hood
→ records actual control flow into a ring buffer
· Trigger traces on a specific function call
· Grab the last few milliseconds before a crash
→ far more useful than only seeing the final stacktrace
· Interactive timeline viewer for zooming through call stacks
· Low overhead: roughly 2%-10% in documented use
· No app changes required to start tracing

Why it matters: If you build latency-sensitive systems, agents, robotics software, infra, or anything with mysterious runtime behavior, magic-trace gives you the “what actually happened?” view. It is especially good for weird one-off slow paths where logs are too vague and traditional profilers blur over the interesting part.

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/3mOpG9El3I

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[INSANE] LongLive 2.0 — NVIDIA’s open infra for long video generation at 45.7 FPS

Long video AI is usually where demos break: short clips, slow sampling, memory pain.

LongLive 2.0 is the repo for builders who want to push past that.

· NVFP4 video generation — 4-bit weights + activations for faster runs
· 45.7 FPS inference reported for long video generation
· NVFP4 KV cache — stores attention memory lighter during generation
· Sequence-parallel training and inference
→ split long video workloads across GPUs instead of choking one card
· Multi-shot video support for autoregressive training
· T2V and I2V workflows
→ generate from text, or condition from images/video-style inputs
· DMD few-step distillation
→ fewer denoising steps, faster generation loops
· Async decoding + streaming VAE placement
→ built for throughput, not just paper demos

Why it matters: LongLive is not just “another video model repo.” It is infrastructure for people trying to make long, controllable, interactive video systems actually run: AI filmmakers, research engineers, robotics sim builders, and indie hackers experimenting with world-generation loops.

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

https://t.co/0glox9CIF2

[RepoCatAI | Sharing GitHub Projects for AI & Robot @repocatai_git]

[BUILDER'S DREAM] Anthropic Cybersecurity Skills — 754 ready-made security playbooks for AI agents

Most agents can write code. Far fewer know what to do when you hand them a memory dump, cloud breach, or suspicious traffic log.

· 754 structured cybersecurity skills your agent can actually follow
· Covers 26 domains: DFIR, threat hunting, malware, cloud, IAM, network traffic, AI risk
· Mapped to MITRE ATT&CK, NIST CSF, ATLAS, D3FEND, and NIST AI RMF
→ one skill can double as investigation guidance and compliance context
· Works with Claude Code, Codex CLI, Cursor, Copilot, Gemini CLI, and https://t.co/JaZKScuhJh tools
· Gives agents senior-analyst style procedure instead of vague “look for indicators” advice
· Useful for building security copilots, SOC agents, pentest assistants, and training labs
· Install with npx or clone it, then point your agent at the skill library

Why it matters: Security work is full of “you only know this if you’ve done it before” judgment calls. This repo turns a huge chunk of that field knowledge into portable agent instructions, so indie builders can prototype credible cyber agents without writing every workflow from scratch.

Follow @repocatai_git for more AI / Agent / Robotics drops 🚀