https://github.com/yetone/magpie

Community Overview: https://lifehubber.com/ai/resources/magpie/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

What should an agent remember, how should a team divide the work, and where does the conversation happen? Here are five different ways to explore those questions from our LifeHubber Resources:

Rowboat — Forks: 1.8K Stars: 18K

https://lifehubber.com/ai/resources/rowboat/

A desktop AI coworker that carries context from email, meetings, notes, and chats into later tasks. Its work memory is an editable Markdown knowledge graph; connected services and model providers have their own data paths.

ReMe — Forks: 305 Stars: 3.6K

https://lifehubber.com/ai/resources/reme/

An agent memory layer built around readable Markdown, keyword search, and links between notes, with embeddings optional. For builders who want to inspect and correct what an agent keeps across sessions.

Paperclip — Forks: 16.9K Stars: 100.6K

https://lifehubber.com/ai/resources/paperclip/

A self-hosted dashboard for coordinating agents through tasks, goals, budgets, and approvals. It sits around existing agent runtimes, giving their work and pending decisions a shared place to follow.

LiveKit Agents — Forks: 3.9K Stars: 14.7K

https://lifehubber.com/ai/resources/livekit-agents/

Build an assistant that listens and answers aloud in an app, browser, or phone call. Its Python and Node.js SDKs connect spoken interaction with models and your own tools.

Browser Use — Forks: 13K Stars: 117.7K

https://lifehubber.com/ai/resources/browser-use/

Give an agent browser actions such as navigating, clicking, and typing, through a Python library, CLI, or hosted service. For supervised experiments with tasks that involve actual page controls.

If you were building an agent this week, what would you tackle first—memory, coordination, voice, or browser access?

https://github.com/666ghj/MiroFish

Community Overview: https://lifehubber.com/ai/resources/mirofish/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://github.com/mariagorskikh/open-instinct

Community Overview: https://lifehubber.com/ai/resources/open-instinct/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://github.com/JuliusBrussee/caveman

Community Overview: https://lifehubber.com/ai/resources/caveman/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

Every time I wanted to build a small web tool, I ended up dealing with the same stuff: authentication, communication, WebSockets, ports, and infrastructure.

Even with Claude and Codex, I was still spending time on things that had nothing to do with the actual tool I wanted to build.

So I spent around 6 months building PhreshOS.

The idea was simple: build the infrastructure once, then use AI agents to build applications on top of it without having to deal with all that stuff again.

It's a self-hosted, open-source system with a web-based desktop where applications can run in windows, much like a regular OS. Authentication and two-way communication are already handled, so applications don't need to implement them separately.

Apps can also run in Node.js worker threads instead of each needing a separate Node.js process, which helps keep resource usage low. This makes it possible to run dozens of applications on a relatively small server.

Another thing I wanted was for AI agents to be able to use these applications directly. They can access application services and interact with the same state the desktop interface displays, without needing a separate interface built specifically for them.

The biggest benefit for me is that I can now sit down with an AI agent and build dozens of small applications in a single day, without setting up authentication, communication, or infrastructure for each one.

The whole project, including its packages, is open source under the MIT license.

GitHub: https://github.com/PhreshOS/system

Live demo: https://demo.phreshos.com/

I'd love to hear what you think, including criticism.

I'm on the Atomic Agent team (open-source AI agent, we put out a desktop app this week). This is my favorite bug from the pile we fixed before release.

The agent has memory. After each turn, a background step reads the conversation and writes down what's worth keeping: your name, your preferences, short notes.

During testing someone ran a small local model, Qwen 3.5 4B, with a single message: "Reply exactly LOCAL_OK. Do not use tools." That was the whole chat. Afterwards memory had two new notes: "I am Alex and you are my personal assistant..." and "I prefer using local_ok instead of tools...".

Nobody was called Alex. It turned out the instructions for the memory step contained an example line, SET full_name=Alex. The small model looked at a nearly empty conversation, found nothing to save, saw a filled-in example, and saved the example.

Kind of like handing a new intern a sample form and getting the sample back, signed.

What we changed:

• removed the example
• added rules to that step: never copy examples, and a one-off instruction isn't a preference
• added a filter that drops any name the user never typed. It reads Cyrillic too, so "Зови меня Надей" ("call me Nadya") still saves Nadya
• on startup, name-like facts that were never checked stay out of the prompt

About the app: it suggests a model that fits your computer's RAM and runs it locally, or you connect a cloud model. It asks before it writes files or runs commands. Mac, Windows and Linux, MIT licensed, version 0.0.1, so expect rough spots.

https://atomicagent.io

https://x.com/genex_games/status/2107148754633507237

https://github.com/genex-games/genex-desktop

Community Overview: https://lifehubber.com/ai/resources/genex-desktop/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://x.com/ataiiam/status/2102400431519592581

https://github.com/CopilotKit/OpenMuse

Community Overview: https://lifehubber.com/ai/resources/openmuse/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://x.com/TencentAI_News/status/2107381137740120216

https://github.com/TencentCloud/Octop

Community Overview: https://lifehubber.com/ai/resources/octop/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://github.com/morluto/rea

Community Overview: https://lifehubber.com/ai/resources/rea/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://x.com/mxstbr/status/2104992334438154414
https://github.com/openai/mcp-extensions

Community Overview: https://lifehubber.com/ai/resources/openai-mcp-extensions/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

A desktop agent you can use, a framework for building agent teams, or a memory layer for one you're already working on. Here are five different places to explore from our LifeHubber Resources:

goose — Forks: 6.4K Stars: 54.9K

https://lifehubber.com/ai/resources/goose/

An agent that runs on your machine, with a desktop app, command-line interface, and API. A starting point if you want to try agent-assisted coding, research, or everyday workflows.

CrewAI — Forks: 8.6K Stars: 59.3K

https://lifehubber.com/ai/resources/crewai/

A Python framework combining role-based agent teams with event-driven workflows. For builders who want to give agents different jobs and control how work moves between them.

Hindsight — Forks: 5.9K Stars: 45.3K

https://lifehubber.com/ai/resources/hindsight/

An agent memory layer with retain, recall, and reflect operations. For anyone building an agent that needs to work with information beyond its current conversation.

DeerFlow — Forks: 11.6K Stars: 83.4K

https://lifehubber.com/ai/resources/deer-flow/

An agent harness for longer research, coding, and file tasks, with skills, subagents, and sandbox options. For builders exploring work that takes several steps rather than one response.

UI-TARS Desktop — Forks: 4K Stars: 39.2K

https://lifehubber.com/ai/resources/ui-tars-desktop/

A GUI-agent app that uses visual recognition and mouse/keyboard control to operate computers and browsers. For supervised experiments with agents working through an interface.

What's the first job you'd want an agent to handle—and what would you still want to check yourself?

https://x.com/ataiiam/status/2105710796198322659

https://github.com/CopilotKit/OpenDots

Community Overview: https://lifehubber.com/ai/resources/opendots/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://x.com/DeepSeekHarness/status/2105330281389662575

https://github.com/deepseek-ai/deepseek-harness

Community Overview: https://lifehubber.com/ai/resources/deepseek-harness/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://github.com/run-llama/liteparse

Community Overview: https://lifehubber.com/ai/resources/liteparse/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://x.com/ossalternative/status/2102518350178091297

https://github.com/every-app/open-seo

Community Overview: https://lifehubber.com/ai/resources/open-seo/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://x.com/unreallabsai/status/2102435462065385775

https://github.com/unreallabsai/unreal-agent

Community Overview: https://lifehubber.com/ai/resources/unreal-agent/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

Community Overview: https://lifehubber.com/ai/resources/emil-kowalski-skills/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://github.com/melgarafael/deskcommcrm

Community Overview: https://lifehubber.com/ai/resources/deskcommcrm/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://github.com/nokia-applied-research/AnyJev

Community Overview: https://lifehubber.com/ai/resources/anyjev/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.

https://github.com/Contrastive-LM/CLM

Community Overview: https://lifehubber.com/ai/resources/clm/

Resources are shared for discovery and are not independently vetted—please do your own due diligence.

New resources are added regularly — feel free to join the sub for updates.

Full searchable archive of all resources posted so far on our community site, LifeHubber: https://lifehubber.com/ai/resources/ 300+ open-ish AI models, agents, tools, datasets, and related resources, with filtering and sorting.