PageIndex (38.4k★, +1,097 today) swaps vector indexes for a reasoning-based table of contents. iFixAi (18.3k★, +340) audits whether an agent actually did its job in under 120 seconds. Octop (6.2k★, +285) is Tencent Cloud's open-source, local-first multi-agent assistant platform. BMAD-METHOD (53.7k★) rewrites agile development into a spec-driven workflow for coding agents. Agno v3.1.0 ships RBAC but needs a stop-the-world migration for its filesystem; Pydantic AI v2.52.0 patches a web_fetch security bug and folds its harness into the main repo.
dots (1.9k★, live for under a day) uses a patched Firefox engine so web agents don't get flagged as bots. context-mode (24.5k★, #1 on Hacker News the day it shipped) cuts tool output by 98% to stretch context budgets. openrig (3k★) runs Claude Code and Codex as one coordinated team. dbx (23.2k★) turns a database client into an MCP server with a built-in AI assistant. universal-modder lets Claude Code mod PC games directly. Claude Code v2.1.286 is versioned as a patch but actually fixes a batch of credential-leak bugs, and Haystack shipped v3.3.0-rc1 fixing an anyio CVE and changing BM25 retrieval behavior.
paperclip (94.5k★) treats agents like employees — org charts, budgets, an audit trail. Orca (81.6k★) lets you run a whole row of coding agents in parallel, each in its own git worktree. Hindsight (42.8k★) splits agent memory into four layers so agents move from remembering to learning. CLI-Anything (51k★) wraps arbitrary software into CLIs agents can call reliably. Cloudflare open-sourced the skill it uses to audit its own code, security-audit-skill (23.2k★), which keeps false positives down by splitting discovery and verification into separate agents. crewAI shipped 1.15.23 with native Gemini 3.8 Flash support, and Claude Code shipped v2.1.285 with a default timeout for long-running background commands.
Z.ai's ZCode (7k★) bundles a desktop shell, a browser UI and an agent CLI into one coding-agent workbench. magpie (1.6k★) is a menu-bar app that switches the underlying model for Claude Code, Codex or Gemini CLI in one click. jevgrep (1.3k★) uses semantic search to hand coding agents the right files up front, cutting some of the back-and-forth grep tokens. golive-skill and agent-console round it out with deployment automation and session observability. Claude Code shipped v2.1.284 today, adding Sonnet 5.5 as the default model plus a batch of terminal fixes.
BuilderIO/agent-native (6.9k★) defines an agent's tools and a human's UI as the same code. yynxxxxx/Codex-X (4k★) wraps the Codex CLI in a desktop GUI. career-ops-hq/career-ops (72.9k★) puts an agent to work on job hunting, running entirely inside your local coding CLI, with no website and no résumé uploaded anywhere. No notable framework release today — Pydantic AI v2.51.0 and Claude Code v2.1.283 were both already covered in yesterday's digest.
Paperclip (86.7k★) manages a fleet of agents like employees — org chart, budgets, heartbeat scheduling. Block's open-sourced Buzz (34.8k★) goes the other way, putting humans and agents in the same Nostr-signed workspace. Z.ai open-sourced ZCode, joining the club of vendors building their own coding-agent shell. mobile-mcp extends MCP tooling to real iOS/Android devices. Notable releases: Pydantic AI v2.51.0 adds OpenAI GPT-Live support and tightens realtime tool_choice / model-id matching; Claude Code v2.1.283 adds a `deniedModels` lockdown setting and `/doctor prompt-audit`.
Nokia's applied research team open-sourced AnyJev, which uses cyclic shifts plus batch prior correction to turn any open LLM into a calibrated decision model with no training — raising auto-decidable traffic from 7.7% to 52.0% in their own benchmark. DSPy 3.4.0 added a TypeSafe client integration with two breaking changes. Pydantic AI v2.50.0 promoted last week's `TypeSafeModel` into a formal `DecisionModel` base class. Also trending: golive-skill, which hands a coding agent the last step of actually shipping to production; magpie, which turns swapping a coding agent's backend model into a menu-bar click; and sno-station, which pairs Claude Code and Codex on one machine and lets them rewrite their own skills.
google/ax runs agent workloads through four Kubernetes-style primitives — Workspace, Task, Gateway, Model — and gained 1,376 stars today; strands-agents/harness-sdk packs lifecycle control, tools, MCP, multi-agent patterns, and memory into a single create_harness() call; HKUDS/CLI-Anything generates agent-native CLIs for any piece of software, sitting at 50,241 stars with an arXiv technical report behind it; vectorize-io/hindsight builds agent memory that claims to learn rather than just recall, citing best-in-class results on LongMemEval and gaining 1,607 stars today; Haystack 3.2.0 adds summarization-based context compaction and token budget control, but removes the `+` operator for combining Toolsets outright.
browser-use/video-use lets Claude Code edit video directly, using ElevenLabs transcripts to find cut points, at 25,702 stars; dream-num/univer repositions its office SDK as an 'Office Harness for AI Agents' and tops today's TypeScript trending; superdesigndev/treg is 'OpenRouter for agent tools,' letting agents call 3,000+ metered tool endpoints with no contract required; davila7/claude-code-templates crosses 30K stars by replacing hand-rolled config with one-line agent/command/MCP template installs; pydantic-ai v2.47.0 tightens type validation so a bad UserPromptPart.content type no longer silently degrades.
Microsoft open-sourced agent-governance-toolkit (6,303 stars), enforcing tool-call policy in code instead of prompts, citing an ICLR 2025 paper showing 100% adaptive jailbreak success on GPT-4o/Claude 3/Llama-3; ai-memory grew from 2,900 to 7,575 stars in a month, giving 20+ coding agent CLIs a shared long-term memory; anthropics/financial-services ships the same finance-vertical agents as both a Cowork plugin and a Managed Agents API template, at 35,728 stars; the official MCP Inspector reached v2.7.0, unifying its web/cli/tui clients into one binary; coder/coder folds AI coding agents into Terraform-defined, controlled dev environments with no API keys in the workspace.
openclaw/openclaw hit 390k stars in ten months, but today's v2026.9.5 release also left some users with vanished sessions that took 8 hours to recover after upgrading; volcengine/OpenViking benchmarks directly against OpenClaw, Hermes, and Claude Code, showing an attached context database lifts long-conversation memory accuracy from 24-57% to 80-83%; trycua/cua shipped CUA-S1-FORMS, a 2.8MB model that takes small decisions like filling in form fields away from the general-purpose model; pydantic-ai v2.46.0 bakes the same 'hand narrow tasks to a specialist decision model' idea into its core API
affaan-m/ECC rode agent-harness optimization to 260k+ stars in eight months, though a growth rate that steep deserves skepticism; cactus-compute/needle trades chat ability for tool-calling precision in an 8-29MB model; Graphify-Labs/graphify builds knowledge graphs with local AST parsing instead of a vector store; tinyhumansai/openhuman makes 'getting to know the user' the core of its agent memory; IvanMurzak/Godot-MCP lets agents drive the Godot editor directly; Claude Code v2.1.277 adds AGENTS.md support
10+ community deep-research skills represent 10+ philosophies of 'how to do research.' From hyperresearch's persistent vault to jamoeight v2's Co-Scientist 6-agent, from adversarial verification to benchmark alignment. This article puts them all on one table.
Seven open-source memory frameworks span the spectrum from auto-extracted vectors to human-readable files: Mem0's one-line add(), Graphiti's bi-temporal knowledge graph, Letta's agent-edited system-prompt blocks, LangGraph's namespaced Store, LlamaIndex's priority-based block truncation, Cognee's triple-store pipeline, and Supermemory's temporal vector-graph engine. This post compares their storage, write/forget mechanics, tenant isolation, and benchmark numbers, then offers selection guidance for four common scenarios.
The deep research open-source ecosystem has evolved from 'single frameworks' to 'tool clusters.' This article compares 12+ projects: GPT-Researcher emphasizes multi-agent collaboration, STORM simulates expert conversations, smolagents focuses on state management. Each tool solves different problems.
alibaba/open-code-review replaces prompt-only review with a deterministic-engineering-plus-agent hybrid, using roughly 1/9 the tokens of a general-purpose agent; cloudflare/security-audit-skill packages Cloudflare's own vulnerability-hunting pipeline into a six-phase skill built around adversarial validation; microsoft/skills bundles 175 pieces of Azure SDK domain knowledge into one-click-install skills and MCP configs; Pydantic AI shipped v2.45.0 and v2.46.0 two days apart, adding TypeSafeModel and a Choices helper
Laguna is Poolside's agentic coding model family: XS 2.1 packs 33B-A3B into a 36GB Mac, while S 2.1 brings 118B-A8B with 1M context to 70.2% on Terminal-Bench 2.1 and 40.4% on DeepSWE, both open under OpenMDW-1.1.
Ant Group's Ling model family deep-dive: 2025→2026 evolution timeline, Ling/Ring/Ming three-series strategy, architecture journey from Ling 1.0 to Ling 3.0, Ling-3.0-flash-Fin finance model, and an Agent developer's selection guide
Nex-N2.5 is Nex AGI's open agentic model family: mini scores 82.9 on OSWorld-G at 35B-A3B, Pro tops Claude Opus 5 with 87.4 at 397B-A17B, and Max leads the whole official table on BrowseComp with 92.6 at 1.6T, all open under Apache-2.0.
NousResearch/hermes-agent bets on a closed learning loop — it grows skills from experience, improves them with use, and remembers who you are across sessions; mksglu/context-mode cuts tool output 98% via MCP + hooks and hit #1 on Hacker News; shinthink/blitzstrike packages recon, static analysis, and live verification into one MCP pentesting server; pliablepixels/gap-trap puts CI gates on vibe coding; Pydantic AI v2.44.0 fixes four security issues in one release, and CrewAI 1.15.22 adds cross-model routing via `llm_overlay`
Cloudflare open-sources security-audit-skill, a six-phase workflow that forces the agent that finds a vulnerability to hand it to a different agent for verification, gaining 1,249 stars on launch day; Vercel ships eve, an agent framework staking a claim next to LangGraph and Mastra; ByteDance's Volcengine open-sources OpenViking, a virtual filesystem that unifies agent knowledge, memory, and skills behind tiered loading; Anthropic open-sources 11 role-specific Claude plugins; Agno v3.0.10 locks shell execution and public MCP access behind explicit opt-in
Alibaba open-sources Open Code Review, replacing pure-agent code review with a hybrid of deterministic engineering and an LLM agent, at 1/9 the token cost of Claude Code Skills; pacifio/atlas brings git-style version control to multi-agent workflows so Claude Code and Codex share checkpoints and memory; alphaXiv/OpenResearch turns any coding agent into a research agent that runs experiments and leaves an auditable trail; JustVugg/colibri treats VRAM, RAM, and disk as one memory tier in a pure-C engine, running 2.8T-parameter MoE models on consumer hardware; no notable framework releases today
CopilotKit/OpenBot gives every AI coworker its own computer, gating every action through policy before it runs; Tencent/teamai-cli syncs skills, rules, and MCP config across a whole team's Claude Code / Codex / Cursor through push-review-pull; VaderChen/YourDesk adds an MCP interface so agents can connect to and drive a real remote desktop; agent-launcher wraps six coding agent CLIs behind one desktop app; AgentVerse-OS gives each project its own isolated Incus workspace that agents are confined to; no notable framework releases today
JustVugg/colibri uses memory tiering across storage/RAM/VRAM to run 744B–2.8T MoE models on consumer hardware in pure C; tech-leads-club/agent-skills wants to get supply-chain verification for agent skills sorted out before they become the next npm trust problem; alphaXiv/OpenResearch turns Claude Code / Codex into experiment-running researchers with git-native reproducibility; calesthio/OpenMontage wraps 12 production pipelines, 100+ tools, and 700+ agent skill files into a full video production framework; alibaba/open-code-review open-sources their hybrid 'rule engine + LLM agent' code review tool; Claude Code v2.1.269 raises the Workflow tool's concurrent agent cap to 256
max-sixty/worktrunk makes git worktree management as simple as switching branches, built for running multiple coding agents in parallel; melgarafael/DeskcommCRM opens a whole CRM to AI agents via MCP, targeting WhatsApp sales; alsk1992/CloddsBot bakes in the x402 protocol so agents can pay each other in USDC, while also bundling 200x-leverage trading into the same chat interface; vxcontrol/pentagi runs fully autonomous agents doing penetration testing inside a Docker sandbox; DSPy 3.4.0 Beta 1 swaps its LM execution layer for a built-in engine, replacing 3.3's experimental types
obra/superpowers hardens a full development methodology into a skill installable across 8+ harnesses; affaan-m/ECC is a performance-optimization system with 68 agents + 286 skills for agent harnesses; cathrynlavery/diagram-design gained 2,286 stars in a single day, swapping Mermaid for 39 editorial diagram types; Tencent's teamai-cli lets a team distribute skill/rule/MCP config centrally; Pydantic AI v2.42.0 adds a GitHub Copilot provider
reverify proves deterministic verification beats asking the model to be careful, with a real binary-reverse-engineering benchmark (97% error rate, all caught); useAgent packages Claude Code/Codex into a cloud AI-coworker platform; bankmcp gives AI read-only access to European bank accounts via PSD2; headcount splits a Claude Code skill ecosystem into a 16-department company structure; Pydantic AI 2.41 and Agno 3.0.8 both shipped today
DeepSeek Harness (dsh) uses an everything-is-a-plugin architecture and hit 214K stars in 3 weeks; ponytail proves with real benchmarks that one skill can cut Claude Code's code output by 54%; Magnitude auto-picks and tunes local models for your coding agent; wigolo gives agents API-key-free web search, crawling, and research
Marker (Datalab open source, Apache 2.0 license, v2.0.0 released 2026-07-20, 39.5k stars) is a pipeline-style document parsing standard library that outputs Markdown and JSON, supports optional LLM boost (`--use_llm`, default `gemini-3.5-flash`), custom formatting logic, table/formula/inline-math/link/reference/code formatting, image extraction and preservation, header/footer removal, and runs on pure CPU, GPU, or MPS (`Apple Silicon`). Unlike [Docling](/posts/tech/2026-09-06-docling-document-parsing) (structured JSON core, dedicated XML exports, pure MIT), Marker centers on Markdown/JSON under `Apache 2.0` with a separate model-weight license (`AI Pubs Open Rail-M`, $5M commercial threshold); unlike [MinerU](/posts/tech/2026-09-05-mineru-ocr-doc-parsing) (custom agreement with MAU/revenue thresholds + attribution obligations), Marker offers a simpler licensing story (`Apache 2.0` code) but requires accepting a separate model-weight license for weights. The series framework ([three-layer model](/posts/ai/2026-08-06-document-parsing-three-layers)) positions all three (`MinerU`, `Docling`, `Marker`) as pipeline-based parsing-layer options with distinct licensing, output, and speed trade-offs.
A close look at three open-source projects training LLMs from scratch in the Chinese community — baby-llama2-chinese (218M, 63.4B tokens), ChatLM-mini-Chinese (0.2B T5, 10.23M dialogues), and Steel-LLM (1.12B, 1T tokens, 8 months) — comparing corpus strategy, tokenizer decisions, and community ecosystem. Honest evaluation included: baby-llama2 scored a bottom-ranking 21 in MiniMind's side-by-side test; ChatLM has the strongest knowledge (62) but weak coding.
OpenELM uses layer-wise scaling to shift parameters toward layers near the output; with 1.08B parameters and 1.5T tokens it beats OLMo 1.2B (+2.36% on the LLM360 average) despite OLMo training on 3T tokens. MiniCPM trains multimodal small models from scratch with a three-stage unfreezing recipe (Resampler first, vision encoder next, everything unfrozen last); MiniCPM-V 4.5 reaches sub-30B SOTA on VideoMME with only 8B parameters, and 4-bit quantization squeezes fp16's 16–17GB memory footprint down to about 5GB for phones.
LitGPT (Lightning AI, ~13,600 stars, Apache 2.0) rewrites 20+ mainstream LLMs — Llama 3, Qwen2.5, Phi 4 — from scratch as single-file, no-abstraction implementations, with a full pretrain / finetune / evaluate / serve CLI. TinyLlama (1.1B parameters, 3T tokens) was trained on this codebase. This post breaks down how it differs from MiniMind, how to actually use it, and where it stops.
MiniMind is an open-source project for training LLMs from scratch: a 64M Dense model and a 198M-A64M MoE model that run the entire chain — Pretrain → SFT → LoRA → DPO → PPO/GRPO/CISPO → Agentic RL — in ~2 hours on a single RTX 3090 at roughly 3 RMB (~$0.40). Every core algorithm is implemented natively in PyTorch with no high-level wrappers.
Switzerland's Apertus (8B/70B, 15T tokens, 1,000+ languages) filters opt-outs and personal data before training to satisfy the EU AI Act; Japan's LLM-jp consortium shipped LLM-jp-4 (12T tokens) in April 2026, claiming wins over GPT-4o and Qwen3-8B on standard benchmarks. Both prove that from-scratch training outside the English sphere is a data-governance problem, not a technical one — plus a note on RWKV-7 as the non-Transformer alternative.
"Open-source LLM" is a spectrum: weights-only (Llama), weights plus data (most fully open projects), or data order, intermediate checkpoints, and training logs all released (LLM360 K2, OLMo 3's model flow). This piece unpacks the two projects that pushed transparency furthest: OLMo 3 shipped the first fully open 32B thinking model in November 2025, and K2 is the first 65B-class model whose checkpoints even include optimizer states.
Open-source projects have pushed the cost of training an LLM from scratch absurdly low: MiniMind runs the full PreTrain-to-RL pipeline for about $0.4 (2 hours on a single RTX 3090), while at the other end OLMo 3 and LLM360 K2 publish everything — data, code, and stage-by-stage checkpoints of 65B models. This series walks the whole project spectrum from $0.4 to 65B in 11 articles, and flags where the map is biased.
Training from scratch only makes sense in three cases: you want to learn how training works, you have 10B+ clean tokens no open model has seen, or you need a fully transparent training process for research. Otherwise fine-tuning or RAG is almost always cheaper. This post collapses the series' main routes into one cost ladder and a decision tree.
YuLan-Mini is a 2.4B open-source model from Renmin University's AI Box lab, trained on 48 A800 GPUs with only 1.08T tokens — scoring 37.8 on MATH-500 and 64.0 on HumanEval, beating Qwen2/Qwen2.5 peer models trained on 7T–18T tokens at math and code. What's public isn't a slogan: per-phase data mixes, pre-annealing optimizer states, and even W&B logs of the ablation studies.
NVIDIA SkillSpector scans agent skills for 71 vulnerability patterns; context-mode sandboxes tool output via MCP to 2% of original size; VoiceStudio runs 16 TTS engines locally with zero cloud dependency; Pydantic AI v2.40.0 adds realtime barge-in and @agent.on_event
Docling (IBM Research Zurich, now governed by the Linux Foundation AI & Data, MIT license, v2.100.0 released 2026-06-09) is an open-source document parsing standard library with structured JSON (DoclingDocument) as its core output. It supports PDF, DOCX, PPTX, XLSX, HTML, EPUB, Apple Pages, video (MP4/AVI/MOV with ASR transcription and keyframes), audio (WAV/MP3), email (EML/MSG), ODF, and XBRL financial reports, with a swappable-stage pipeline parser (pure CPU or GPU-accelerated), VlmPipeline option (GraniteDocling 258M VLM), MCP server and API server (docling-serve), and native integrations with LangChain, LlamaIndex, Crew AI, and Haystack.
mattpocock/skills gained 2,757 stars in a single day — the fastest-growing repo on GitHub today. Anthropic's own anthropics/skills and the open-source coding agent anomalyco/opencode are trending alongside it. Meanwhile MCP server reverify ran a benchmark on 71 real Windows system files and found AI has a 97% error rate reverse-engineering binaries from memory — deterministic tools caught every single one. On the framework side, pydantic-ai, agno, and haystack all shipped routine patches today, nothing major.
Thinking Machines Lab (founded 2025 by Mira Murati, $2B seed at a $12B valuation) released Inkling in July 2026 under Apache 2.0 (975B total / 41B active params, 1M context, native multimodality, controllable thinking effort) plus a smaller Inkling-Small (276B / 12B), paired with the Tinker fine-tuning platform—turning customizability itself into the product.
github/spec-kit turned one and shipped 1.0.0, with its maintainer stressing that adaptability now matters more than stability. stablyai/orca lets you run a whole fleet of coding agents in parallel worktrees and gained 812 stars in a single day. KeygraphHQ/shannon shipped 3.0, an AI agent that runs real penetration tests and outputs SARIF reports straight into CI/CD. On the browser side, ChromeDevTools/chrome-devtools-mcp opens Chrome's official MCP server up to any agent. On the framework side, Pydantic AI v2.38.0 changes how one-off capabilities get merged (a breaking change), and Claude Code v2.1.259 fixes a long-standing bug where concurrent sessions silently clobbered each other's settings.
NousResearch/hermes-agent keeps climbing (239,994 stars) on a self-improving learning loop that remembers how to use your tools and who you are across sessions. pacifio/atlas gained 895 stars in a day by giving multiple coding agents shared, traceable version control — every commit links back to the session that made it. blader/humanizer strips the AI tell from writing using 35 patterns, without inventing facts. On the document side, firecrawl/pdf-inspector decides in under 50ms whether a PDF needs OCR, and superlinked/sie folds every model an agent needs into one self-hosted inference cluster. On the framework side, AG2 v1.0.3 ports fully to MCP 2.0 (a breaking change) and adds TealTigerMiddleware, a deterministic, non-LLM prompt-injection guard.
openclaw/openclaw, a self-hosted personal assistant, has climbed to 388k stars by wiring WhatsApp, Telegram, Slack and other chat channels into one Gateway. The same week, NVIDIA shipped SkillSpector, which scans Claude Code, Codex, and MCP skills for 71 vulnerability patterns — research it cites found 26.1% of skills contain vulnerabilities and 5.2% show likely malicious intent. Also today: stablyai/orca turns parallel multi-agent coding into a full IDE, and VectifyAI/PageIndex challenges the assumption that RAG needs a vector database with a reasoning-based tree index. claude-code v2.1.257 adds a Containment Escape security rule, and agno v3.0.5 stops swallowing embedding failures silently and starts reporting them honestly.
HKUDS/nanobot hit 47.5k stars in half a year, demonstrating the 'small core + multi-channel + long-term memory' formula for a self-hosted personal agent; zhayujie/CowAgent (formerly chatgpt-on-wechat) reinvents an old chatbot wrapper as a full Agent Harness with a three-tier memory architecture and a nightly 'Deep Dream' distillation pass; conductor-oss/conductor wires a durable-execution graph engine to native MCP tool calls, letting an agent's loop survive a crash or a weeks-long human approval wait; mksglu/context-mode goes straight at the pain point of MCP tool calls flooding the context window, and hit #1 on Hacker News. agno v3.0.4 is the only framework release that clears the bar — it flips KnowledgeManagementTools' ingest_path to opt-in by default to close a security gap.
can1357/oh-my-pi forked the well-known coding agent 'Pi' and, by obsessing over tool-call formats, pushed Grok Code Fast 1's task success rate from 6.7% to 68.3%; K-Dense-AI/scientific-agent-skills opens 163 research skills to any agent that supports the Agent Skills standard; addyosmani/agent-skills packages a senior engineer's six-stage workflow into a skill set and hit 90k stars in a week; THU-MAIC/OpenMAIC v1.0.0 adds a conversational Pro workbench, landing multi-agent orchestration in the concrete vertical of course content production. On the framework side, agno v3.0.2 is the one release that clears the bar: it publishes Agents/Teams/Workflows as named MCP tools and ships several breaking changes along the way.
Treat pi as a black box first: 4 run modes, session tree persistence, mid-conversation model switching, Enter vs Alt+Enter message interjection, /tree branch navigation. Builds intuition for the architecture parts that follow.
Why Pi has no built-in permission system, Gondolin Extension (micro-VM), Docker mode, OpenShell policy-controlled sandbox, permission model philosophy, three containerization patterns, security boundary comparison, micro-VM vs container vs process isolation.
Complete Extension system analysis: Extension interface definition, onLoad/onUnload lifecycle, four major Hooks (onAgentStart/onBeforeToolCall/onAfterToolCall/onTurnEnd), five extension points (tools/commands/keybindings/ui/settings), ExtensionRunner load order and dependency resolution, ExtensionAPI capabilities, Dynamic Border, Widget, Dialog, Selector UI components, Extension inter-communication, hot reload mechanism, official example Extensions.
From user-visible features into architecture: 7 npm packages with clear boundaries, one-way dependency flow, why pi-tui/pi-telemetry have zero deps, how pi-ai encapsulates provider details, lockstep versioning avoiding diamond deps. Builds an 'outside-in' mental model.
This 17-part series takes you from CLI user perspective through pi-mono's Agent Loop, Session Tree, Tool System, Extension System, TUI Architecture, Remote Session, Telemetry, Compaction, and Release process. Ideal for developers wanting to self-host agents, research agent architecture, or contribute to pi.
I'm building my own Python coding agent called looplane. This series dissects the source code of five mature projects — pi, oh-my-pi, opencode, codex, and claude-code — topic by topic, while also comparing them with Looplane's current TUI, external CLI runtimes, local gateway, usage/OTel/session tooling, and Cloudflare slice. Every post follows a fixed five-part structure: design problem → how five projects do it → looplane's choice → academic grounding → improvement roadmap, with evidence cited at file#symbol level.
Google's own ChromeDevTools/chrome-devtools-mcp (50k stars) lets coding agents drive a real Chrome instance for performance profiling and debugging; abhigyanpatwari/GitNexus replaces 'guessing at code by reading it' with a pure browser-side knowledge graph; mksglu/context-mode targets coding agents' context-window waste; google/skills is Google's own official Agent Skills package library; livekit/agents keeps shipping actively for voice agents. On the framework side, pydantic-ai v2.36.0 adds `@durable_operation`, opening a pluggable slot for third-party durable-execution engines.
screenshot-to-code is not a one-shot screenshot-to-HTML tool. Its core is a 30-step Agent Loop with 7 tools — extracting real assets from screenshots, self-verifying with Playwright, and running 4 models in parallel so users pick the best output. 74,500+ GitHub stars, MIT License.
calesthio/OpenMontage turns a general-purpose coding agent into a full video-production studio with 12 pipelines and 700+ skill files, jumping to 50k stars this week; Anthropic's own official plugin marketplace claude-plugins-official gained +292 stars in a single day; rohitg00/agentmemory gives coding agents cross-session memory via BM25 + vector + knowledge graph retrieval, claiming 95.2% R@5 on its own LongMemEval-S benchmark; sodiumsun/agenttrail builds a local, real-time task map for Claude Code, Codex, and Cursor. No major framework releases today.
thedotmack/claude-mem lets context survive across sessions via compressed memory, crossing 90K stars; volcengine/OpenViking unifies memory, RAG, and skills into a virtual filesystem browsable over the viking:// protocol, up 3,078 stars this week; apache/maka enters the Apache Incubator, turning an agent's execution history into a replayable event-sourcing log; K-Dense-AI/scientific-agent-skills lets 175,000 scientists turn a general coding agent into a domain expert with 163 skills. Haystack v3.1.0 adds AgentTool for multi-agent delegation.
deepseek-ai/deepseek-harness (dsh) uses a Cordis plugin architecture to make models, tools, sandboxes, and memory all swappable components, hitting nearly 200k stars a week after its developer preview launch; PrimeIntellect-ai/prime-agent runs long-lived research coding tasks on a Recursive Language Model architecture, surviving terminal disconnects via a persistent IPython session; liqiwa/mcp-radar automates this very kind of digest by scanning GitHub daily for newly ranked MCP servers. On the framework side, Mastra 1.61.0 adds a crash-resilient background task queue, and ComposioHQ/composio 0.17.0 extends SSRF protection to tool-execution downloads and S3 uploads.
The same model can score 20 points apart on different harnesses, 32% of SWE-bench Pro verifier judgments were found to be wrong, and DeepSWE's 113 tasks make most models score zero. This guide decodes six major coding benchmarks — what they test, which are easy to game, and which ones you should care about.
Nearly every frontier open-source model in 2026 is MoE: Ornith 35B activates only 3B to beat 31B dense models, MiniMax M3 uses 456B total but 45.9B active to hit SWE-bench Pro 59%, DeepSeek V4 runs 1.6T total with 49B active. This post explains why MoE dominates coding and agentic benchmarks using four case studies.
Allen AI's OLMo is the only language model family that fully publishes weights, training data (Dolma, 9.3T tokens), training code, all intermediate checkpoints, and evaluation tools. OLMo 3's 32B Think model hits 96.1% on MATH — and you can use OlmoTrace to trace any output back to the exact training data that produced it.
'Open-source' in AI doesn't mean what it means in software. MIT and Apache 2.0 let you do almost anything; the Llama License requires a separate deal above 700M MAU; old Gemma terms let Google change rules unilaterally (Gemma 4 switched to Apache 2.0). This guide maps what you can and can't do by license type.
Three non-big-lab teams used different RL post-training strategies to produce benchmark dark horses in 2026: Ornith's self-improvement loop (GRPO), Nous Research's DataForge + Atropos execution-reward RL, and MiniMax's massive-scale RL across 200K real environments. Different strengths, but one shared proof point: post-training RL matters more than pretraining scale.
tinyhumansai/openhuman uses a local-first Memory Tree to compress your digital life and orchestrate multiple agents, already at 37k stars in early beta; Vercel Labs' fx is a native coding agent CLI written in Zig at under 8 MiB; NVIDIA open-sources labs-OO-Agents, packing an agent's prompt/tool/workflow into a single Python class; CopilotKit/OpenBot containerizes agents with governance gates — every action is reviewed before execution. Agno v3.0.0 is a major breaking release requiring database migration, and Haystack v3.1.0 adds multi-agent delegation via AgentTool and context compression via CompactionHook.
MiniMax started as a consumer chat app company, then M2.5 scored 80.2% on SWE-bench Verified at 1/10-1/20 the cost of Claude Opus; M3 (456B total / 45.9B active) became the first open-weight model to clear 59% on SWE-bench Pro, with 1M context powered by their novel Sparse Attention mechanism.
Nous Research doesn't pretrain — they fine-tune and do RL. Hermes 4 scores 96.3% on MATH-500, NousCoder-14B improves Qwen3-14B's coding ability by 7% using only 24K training samples. But the real moat is Hermes Agent: 236K GitHub stars, #19 globally, 3,000 contributors.
DeepReinforce's Ornith 1.5 family, trained with self-improvement RL: the 397B flagship scores 86.0 on SWE-bench Verified, matching Claude Opus 4.8; the 35B-A3B activates only 3B parameters per token yet leads every coding benchmark in its class; the 9B runs on phones. MIT-licensed, fully open-source.
Panniantong/Agent-Reach wraps yt-dlp, twitter-cli and friends behind a single CLI so agents can read Twitter/Reddit/YouTube/Bilibili; LangChain ships deepagents, a batteries-included harness with filesystem access, sub-agents, and skills; Tracer-Cloud/opensre frames AI SRE agents as a scored RCA benchmark; Anthropic's claude-plugins-community marketplace adds a review pipeline for community plugin trust, gaining +490 stars in a single day. GitHub Copilot CLI v1.0.81-8 (pre-release) adds Grok 4.6 xhigh reasoning and live plugin hot-reload.
Stanford Marin pre-registers a paloma macro-loss of 2.04 with a 5-rung Scaling Ladder at 1% cost, then trains 535B-A23B on 11×GB200 in public with live W&B telemetry — 847 training buckets already show the most teachable frontier run.
duty1g/x64dbg-mcp-server wraps a reverse engineering debugger as MCP tools, hitting 563 stars in two days; Cripacx/mediagen bakes EU AI Act content marking into an image generation MCP server; QwenLM/qwen-code v0.22.0 publishes full SWE-bench Verified test trajectories with a 77.08% pass rate; open-gitagent/gitagent rewrites its core engine in Rust with agent state living entirely inside a git repo. On the framework side, GitHub's official MCP Server v1.10.0 is a security spring-cleaning — a typo in `--tools` now crashes the server on startup.
DeepSeek used MLA and MoE innovations to drive inference costs to an industry low. V4 Flash activates only 13B parameters while approaching frontier-model quality and ranks first by OpenRouter usage. This guide traces V1 through V4, the R1 reasoning branch, and how to choose each version.
GLM is Zhipu AI (Z.ai)'s open LLM family from Tsinghua's KEG Lab. GLM-5.3 (2026/08) lifts coding +50% over the previous generation, hits 84.5% on CyberGym ahead of Anthropic Mythos 5 and OpenAI GPT-5.6 Sol, and scores 60 on the Artificial Analysis Intelligence Index tied with Kimi K3 for open-source #1. The only frontier open model trained entirely on Huawei Ascend.
Grok is xAI's LLM family: founded July 2023, opened with a 314B MoE under Apache 2.0 in March 2024, and two and a half years later spans Grok 4.6 (500K, $2/$6, four reasoning levels), Grok 4 Fast (2M), Imagine for image/video, and Grok Build for terminal coding — its moat is distribution (X / grok.com / Tesla / Bedrock), not single-model supremacy. This post traces Grok 1→4.6, sub-line positioning, pricing, and licensing traps.
Kimi is Moonshot AI's LLM family, born from ultra-long context. Kimi K3 (2026/07) is the world's first open 3T-class model—2.8T params, 104B active, 1M context, scoring 60 on the Artificial Analysis Intelligence Index tied with GLM-5.3 for open-source #1. Its Kimi Delta Attention brings a 2.5× scaling efficiency gain.
Llama is Meta's open-source LLM family, with the largest enterprise deployment footprint and the most mature ecosystem. Llama 4 Scout (10M context) and Maverick (17B active / 400B total MoE) are the current open multimodal benchmarks, but Meta pivoted to closed-source Muse Spark in April 2026—Llama 4 is likely the last major open Llama, and its license is not truly open (Llama 4 Community License, separate license required above 700M MAU).
Mistral is Europe's most successful AI startup, cutting through the market with a 'smaller, faster, cheaper' strategy and European data-sovereignty positioning. Mistral Large 3 is Europe's strongest commercial LLM, Small 4 is the 24B efficiency king, and Medium 3.5 is the open Modified-MIT model optimized for agentic coding. Its moat is not technical scale but the 'European compliance' card.
Qwen is the most-downloaded model family on HuggingFace, spanning sizes from 0.8B to 2.4T. In August 2026, Alibaba open-sourced a Max-tier flagship for the first time (Qwen3.8-2.4T-A95B) — but swapped the customary Apache 2.0 license for custom terms. Meanwhile the other new release, Qwen3.8-27B, runs native vision on laptop-class hardware and is the only one shipping under Apache 2.0. This post traces the family from 2023 through generation 3.8, explains how the open line and the commercial line split apart, and helps you pick the right model at each tier.
In 2026, AI models span seven major categories and more than 20 subcategories. This introduction to the AI Model Families series maps use cases to models and models to families, with current rankings and selection advice for each use case.
CopilotKit/OpenBot ships an AG-UI-based 'AI coworker' framework where each agent gets its own computer, hitting 2,289 stars in a week; Bruno's official MCP server (usebruno/bruno-mcp) arrives two months after the community version (Ostico/bruno-mcp-studio); the browser-use team spins off a macOS Harness project that gives LLMs six accessibility primitives to control a Mac directly; opencode, now under Anomaly, has ~199K stars — surpassing Anthropic's Claude Code at ~142K. On the framework side, the MCP TypeScript SDK v2 splits the monolith into 8 sub-packages and follows the protocol's stateless redesign, dropping the session handshake entirely.
In August 2026, it's not just five frameworks moving. Beyond OMP 2, Pi v2, Opencode 2, dsh, and Claude Code, three model makers — Google (Antigravity CLI), Meta (Muse Code), and xAI (Grok Build) — are building coding agents directly. Add Amp, Cline 2.0, and the Codex CLI Rust rewrite, and eight-plus frameworks are undergoing architecture-level changes simultaneously. Factor in 110+ total CLI tools, and H2 2026 is a divergence period for harness methodology. This article analyzes four architectural approaches, one shared direction, and one emerging trust crisis.
Helicone is an open-source LLM gateway and observability platform: requests sent through its compatible endpoint automatically capture model, latency, tokens, cost, and custom properties, while managed credits or BYOK enable routing and fallbacks.
Volcano Engine's open-source OpenViking stores agent memory, knowledge, and skills as a viking:// virtual filesystem — browsable with ls, tree, and find. Three-tier loading (L0/L1/L2) averages just 550 tokens per retrieval, boosting LoCoMo memory accuracy from 24–57% to 80–83%.
Steel packages Chromium sessions, CDP, proxies, stealth, and debugging behind an Apache-2.0 browser API. Its public repository has about 7,400 stars and it entered the Stripe Projects developer preview in 2026. Self-hosting fits development and data-control needs; Cloud addresses concurrency, managed proxies, CAPTCHA, recordings, and SLAs.
HKUDS/nanobot rode its v0.3.0 'The Agency Release' to 47K stars in 7 months as a self-hostable personal agent runtime; genspark-ai/genoffice hit 3,400 stars in 3 weeks with an open-source AI office suite for native file formats; NVIDIA published labs-OO-Agents (NOOA), collapsing agent state into a single Python class; repo-context-mcp is an MCP server that helps coding agents understand repos without stuffing the entire codebase into the prompt. Framework-wise, Mastra 1.60.0 adds durable execution and Cloudflare Sandbox; pydantic-ai v2.33.0 has a breaking change from the anthropic SDK's switch to httpx2.
DeepSeek Harness (dsh) is DeepSeek's official open-source coding agent framework, released as a v0.1 developer preview on 2026-08-13, accumulating 184,000+ stars in 9 days. Its core is the Cordis plugin kernel — model adapters, tools, agent loop, and UI are all swappable plugins. Four runtime modes, with the ability to use Claude Code and Codex as sub-agents. Web UI first, no native CLI.
OMP 2 is no longer a Pi fork. The entire codebase has been rewritten from scratch in Rust, with ~41 crates covering a custom bash engine, GPU-accelerated GUI, embedded CPython 3.14t, gRPC transport, and Kokoro-82M TTS. Currently in pre-release with no stable version yet.
Opencode 2 is a major rewrite led by Anomaly (Dax Raad). Runtime migrated from Bun to Node.js (memory issues), desktop from Tauri to Electron (WebKit perf and Node integration), v1 API intentionally incompatible. New: multi-tab parallel sessions, persistent backend service, HTTP API + SDK. Currently beta, stable estimated ~September 2026. ~200K stars.
Pi v0.84.0 (2026-08-06) promotes the AgentHarness v2 API to stable. Lane-based v4 Session model makes operations durable and interruptible. CBOR replaces JSON, Unix sockets replace HTTP. Earendil Inc. (Armin Ronacher's PBC) behind it has secured initial funding. 95.4K stars, still MIT, still minimal.
Tavily and Exa are cloud-only APIs and can't be self-hosted. What you can assemble instead is SearXNG (269 upstream engines, 82 on by default) plus Crawl4AI (78.8k stars, Apache-2.0), and the ready-made Tavily-compatible wrappers are all still double-digit-star solo projects you should not depend on. But SearXNG has no index of its own, and running it from a datacenter IP gets you empty results — those two facts decide whether self-hosting is worth it.
Cursor open-sources its official plugin marketplace cursor/plugins, standardizing the ecosystem with plugin.json + skills + MCP definitions (+470 stars in one day); apache/maka enters the Apache incubator with an append-only event log recording every tool call and permission decision for auditable local-first agent workbenches; magnitudedev/magnitude auto-detects hardware, downloads, and runs models locally out of the box for offline agents; vercel/eve puts agent capabilities into convention directories like tools/, skills/, and schedules/ — the filesystem is the interface. On the framework side, pydantic-ai ships a v2.32.1 patch.
Supabase isn't just an open-source Firebase alternative — its core design builds Auth, Storage, and Realtime entirely on PostgreSQL schemas and WAL. The result: everything is queryable with SQL, pgvector works out of the box, and AI agents can operate the entire platform by writing SQL. 108k GitHub stars, Apache 2.0, free tier with 500 MB database.
Volcengine (ByteDance) open-sources OpenViking, replacing black-box vector search with a viking:// virtual filesystem for agent memory — benchmarks show 80%+ accuracy while saving 34-91% tokens. munder-difflin wraps multiple coding CLIs into a desktop office with shared memory; ai-memory solves cross-CLI amnesia with a Rust MCP server; mukul975's cybersecurity skill pack rockets to ~28K stars in a day. pydantic-ai v2.32.0 adds OpenRouter/xAI attachment search and instrumentation improvements.
DeepSeek's open-source agent harness 'dsh' crossed 20K stars within an hour of its 8/13 launch and has since accumulated ~158K stars, with 2000+ plugin proposals flooding in within two days. Its core is a Cordis-powered 'everything is a plugin' architecture that can even call Claude Code and Codex as sub-agents. RightNow-AI reimagines agents at the OS level with Rust (openfang), NetEase Youdao ships a desktop Agent built on OpenClaw (LobsterAI), and PrimeIntellect's prime-agent features a self-improving reasoning loop. CrewAI 1.15.16 adds execution context tracking and flow error logging.
Aider is a terminal AI pair programmer dating back to 2023 (Python, Apache-2.0, ~48.3k stars), designed against the grain of today's autonomous agents: you control context by hand with /add, every edit becomes its own atomic git commit, and architect/editor mode splits planning from editing across two models. But note the maintenance cadence: the latest PyPI release is 0.86.2 from 2026-02, the last commit was 2026-05, and the site still recommends Claude 3.7 Sonnet and o1.
omp is a fork of Pi, but it is not just a plugin layer stacked on top: it adds roughly 80,000 lines of Rust, pulling grep, shell, AST, and PTY in-process. Built-in tools go from Pi's 7 to 31, plus 14 LSP ops, 28 DAP ops, and 60+ providers. One codebase, two opposite bets.
OpenClaw has 386k stars to Hermes Agent's 232k, yet Hermes passed it on OpenRouter daily tokens back on 2026-05-10 (224B vs 186B). The nine self-hosted agents that appeared this year aren't nine competitors — they're nine incompatible answers to one question. CVE-2026-44112 broke OpenClaw's own sandbox, and in the Meta alignment director's inbox incident there was no attacker at all: context compaction ate the safety instruction.
headroom compresses tool output, logs, and RAG chunks locally before sending them to the LLM, reaching 66K stars in 7 months. agentmemory gives Claude Code, Cursor, Codex CLI and a dozen other coding agents a shared cross-session memory store, hitting 27K stars in half a year. Andrew Ng's team releases OpenWorker, a desktop agent targeting knowledge workers beyond engineers. NVIDIA's labs-OO-Agents reimagines agent abstractions with object-oriented design. Mastra 1.59.0 renames CostGuardProcessor to TokenCostControl (breaking). browser-use 0.13.8 adds first-party OpenClaw skill support.
forge adds a reliability middleware layer for tool-calling on self-hosted LLMs, proxying opencode/aider/Claude Code with zero code changes; repo-context-mcp provides token-budgeted repo context packaging via MCP, integrated into PR CI within 5 days of launch; DeepSeek's official harness dsh spawned at least 5 independent community desktop wrappers in one week, totaling nearly 1,500 stars; Microsoft Research's browser agent framework Webwright uses Skill Factory to distill solved tasks into replayable scripts without model calls, boosting reuse accuracy by 15 percentage points on WebArena; Mastra 1.59.0 renames CostGuardProcessor to TokenCostControl (breaking); Pydantic AI v2.30.0 patches a DNS rebinding security vulnerability in its local web chat interface.
A VS Code extension open-sourced by Microsoft employees that reads your local Claude Code / Codex / OpenCode session logs. The real payload is 45 Markdown rules: prompts under 30 characters, sending the next message within 15 seconds of receiving 20 lines of AI code, instruction files over 4,000 bytes — turning 'context engineering' into numbers you can argue with.
I tested 10 open-source PDF parsing tools on four scanned NTU graduate entrance exams. VLM-based tools—Firecrawl, MinerU 3.4, and Marker v2—overwhelmingly beat conventional OCR on formulas and code, but installation was the real barrier: MinerU's old package name creates dependency hell, Marker's first model download takes 10 minutes, and PaddleOCR needs a separate engine. In practice, use RapidOCR for screening and MinerU or Firecrawl for close inspection.
Vercel ships eve, a filesystem-first TypeScript agent framework tightly coupled with its AI Gateway/Sandboxes; Prime Intellect's Prime Agent treats the entire conversation context as program variables with a self-modifying Continual Harness; aden-hive's Hive replaces pre-compiled execution graphs with 'clone the Queen'; HKUDS's nanobot hits 47k stars in six months with its v0.3.0 Agency Release. No major version bumps on the watchlist today.
The 2026-08-13 release added 363,246 lines and published the For You ranking weights for the first time: favorite 0.5, reply 5.0, report −234.0. But the weights are constants — the P(action) that actually decides order comes from a 2560-dim, 8-layer transformer.
After cloning and building both, three things differ from the stereotype: ArduPilot's EKF3 header credits the derivation to PX4/ecl, so the hardest layer is shared; PX4's last year of commits comes from company domains (380 from Auterion alone) while ArduPilot's comes from personal addresses with one contributor at 37%; and what really decides the choice is not performance but BSD-3 versus GPLv3, and which layer you need to modify.
Firecrawl's open-source Rust conversion library turns 14 office formats (including legacy .doc / .ppt / .xls) into GFM at a 4.7ms median — 109× faster than Docling under the same timing basis. The trade-off: it does no OCR at all.
Scans and complex layouts leave you no choice but to infer structure with a model. But the technical gap between MinerU, Marker, and Docling is far smaller than the licensing gap — MinerU needs a separate license past $20M monthly revenue, Marker's model weights need payment past a funding threshold, and only Docling is cleanly MIT. Read the LICENSE before the benchmark.
The most common mistake in feeding documents to an LLM isn't picking the wrong tool — it's picking the wrong layer. Structure already in the file goes to the conversion layer (milliseconds); text without structure goes to extraction; only inferred structure needs parsing. anydoc's 4.7ms against Docling's 513.6ms is a 109× gap, and most people jump straight to the most expensive layer.
Digital-native PDFs already contain readable text — what's missing is structure, and heuristics can recover it. PyMuPDF, pdfplumber, pypdf, and Tika do this with zero GPU and zero inference cost. The biggest selection trap isn't accuracy; it's PyMuPDF's AGPL-3.0 license.
Koboyo claims close to 90,000 free hand-drawn SVG icons (the count oscillates: 92,967 → 87,954 → 90,150), but its sitemap only lists about 17,930 icon pages, and its license page explicitly forbids building an icon library or canvas app with them. There are actually three routes to a hand-drawn look: collect a library, bend existing geometry programmatically (sketchyicons turns every straight run in Lucide into a quadratic Bézier, seeded by icon name for byte-for-byte reproducibility), or generate with AI. This piece compares seven libraries on scale and license, unpacks the algorithms behind sketchyicons and tldraw, and surveys the icon search tools now shipping MCP servers.
From MarkItDown (175k stars, MIT) to curl_cffi (6k stars), a survey of 34 open-source tools for feeding data to AI. Categorized along five axes: whole-site crawling, AI browser agents, document conversion, smart extraction, and anti-detection infrastructure. The key to selection isn't which tool is best — it's scenario matching.
HeyGen's open-source HyperFrames defines video timelines with HTML data attributes, uses headless Chrome for frame-accurate seek-and-capture, then encodes via FFmpeg to MP4. 33k stars in 3 months, Apache 2.0, 21 agent skills — AI agents write HTML to produce video, no React needed.
From the CLI tool kin3o to the CVPR 2026 paper OmniLottie — a survey of open-source approaches for converting text and images into Lottie animations, with performance benchmarks and selection guidance.
AI agents running tests are non-reproducible; hand-written Playwright is hard to maintain. Four tools that emerged in 2024-2025 each tackle this dilemma with very different design philosophies.
Anthropic shipped Claude Design on 2026-04-17. On 4-28, nexu-io/open-design went public -- same artifact-first loop, Apache-2.0, runs on the 16 coding-agent CLIs you already have. Two weeks from 0.1 to 0.7, 40k+ stars. A paradigm shift that flattens AI design tools from vertical SaaS into a skill bundle.
asgeirtj/system_prompts_leaks collects the raw system prompts of 40+ AI assistants, from GPT-5.5 and Claude Opus 4.7 to Gemini 3.1 Pro, with 40.3k stars, 461 commits, and an MIT license. The value isn't in obtaining secrets -- it's in turning vendors' implicit policies into comparable engineering material. What you should study is the design decisions, not the text itself.
Warp evolved from a Rust-powered modern terminal into an AI Agent-integrated development environment (ADE), open-sourced under AGPL in April 2026, with over 700,000 developer users.
goose is an open-source AI Agent maintained by the Linux Foundation's AAIF, supporting 15+ LLM providers and 70+ MCP extensions, built with Rust as a Desktop App + CLI + API. It positions itself as a vendor-neutral, self-hostable alternative to Claude Code.
AEO/GEO tools aren't a single category — they span three distinct layers: the input layer (is your website ready for AI to read), the traffic layer (how much are AI bots actually crawling), and the output layer (how is your brand mentioned in AI answers). This post maps out all three layers, from open-source self-hosted options to commercial SaaS.
DeerFlow is ByteDance's open-source Super Agent Harness built on Python 3.12 + LangGraph. It orchestrates long-running tasks through sandboxes, long-term memory, sub-agents, skills, and a messaging gateway. It hit #1 on GitHub Trending in February 2026, now surpassing 63,000 stars, with support for Telegram/Slack/Feishu, Claude Code integration, and multiple search backends.
An open-source coding agent reference implementation from Vercel Labs. A three-layer architecture separates the web UI, agent workflow, and sandbox VM — designed as a starting point for teams that want to self-host their own Claude Code or Cursor Background Agent.
Claw Code is a from-scratch Rust rewrite of the Claude Code CLI, featuring 48K lines of code, 40 tools, and MIT licensing. Most remarkably, the entire project was built by multiple AI agents collaborating over just 5 days, surpassing 170K GitHub stars within a week of launch.
An open-source Agent Harness framework from HKUDS (HKU Data Science Lab) that implements tool calling, skill loading, memory, permissions, and multi-agent collaboration as complete infrastructure, supporting Anthropic / OpenAI / GitHub Copilot API formats.
OpenCode is a free, open-source TypeScript CLI agent (MIT, ~198K GitHub stars). It supports 75+ model providers including local Ollama, allows authentication via Copilot/ChatGPT accounts, and lets you switch models mid-session without losing context. There is also a desktop app and an official Zen gateway.
2026 Q1 saw a full-blown open-source model explosion: on the LLM front, GLM-5, Kimi K2.5, and Qwen3.5 caught up with closed-source models; Embedding and Reranker are dominated by Qwen3 and BGE; speech has Voxtral TTS and Whisper V3; image has FLUX.2; and video has Wan 2.2 rivaling Sora. This is the complete navigation map.
Codex CLI is OpenAI's open source terminal coding agent (Rust, Apache-2.0, ~106.6k stars) with MCP, subagents, image input, code review, and Skills. The model line is now GPT-5.6 Sol / Terra / Luna, and the desktop app, CLI, and IDE extension share one config.toml.
Gemini CLI is Google's open source terminal AI agent (Apache 2.0, ~106.6k stars). It once offered 60 requests per minute and 1,000 per day for free, with a 1M context window. The individual tier stopped serving on 2026/6/18 and Antigravity CLI took over. The project isn't shut down — the repo is still maintained — but it now serves only Gemini Code Assist Standard/Enterprise licenses and paid API keys.
OpenCode is an open-source AI coding agent written in TypeScript (MIT, ~198K GitHub stars, repo at anomalyco/opencode) with a built-in TUI, 75+ LLM providers, LSP integration, a Vim-style editor, SQLite session management, and a desktop app. Free, no subscription, local or cloud models.
Pi is a minimalist coding agent by Mario Zechner (TypeScript, MIT, ~93K stars) with just 4 core tools and a very short system prompt — everything else you add yourself via Extensions, Skills, and Prompt Templates. It deliberately omits MCP, sub-agents, plan mode, and permission popups. The repo is now earendil-works/pi and the npm scope is @earendil-works.