579 tools and products — trending open source, and what gets used in AI and other work.
FrontierAgent is an open-source agent runtime, terminal product, and evaluation suite for long-horizon research and file-based work. Its native terminal TUI provides a ReAct workflow in which one stateful agent researches, reads files, writes deliverables, runs commands, and iterates in a task-scoped sandbox, and an Agent Team workflow in which a coordinator maintains a task board, delegates bounded independent assignments to parallel sub-agents, collects structured reports, and synthesizes the result. Shell and file tools use a shared sandbox with read-only /inputs, working-state /workspace, and persistent /outputs directories. The TUI supports queued instructions during execution, approval-required diffs for mutating operations, local action traces, checkpointed sessions, resumption, and reversion. The same workflow engine powers a subprocess benchmark runner with deterministic artifact collection, concurrency, progress inspection, and reruns of individual failures. The repository also documents connection to the OpenAI-compatible Apodex-1.1 endpoint through the Apodex API.
ai-memory is an open-source local server for long-term memory and session handoff among AI coding agents. It captures prompts, tool calls, and agent context through MCP integrations and lifecycle hooks, storing the material in a searchable, Git-backed Markdown wiki. When a session ends or is explicitly finalized, it generates handoff context for a subsequent session, including the project architecture, failed approaches, and open questions, so work can continue across agent vendors without restating the context; clients without a true session-end hook use explicit finalization commands. The project documents integrations for Claude Code, Codex, Command Code, Devin CLI, OpenCode, Cursor, Gemini CLI, Oh My Pi, Pi, and Crush, with agent-specific configuration, generated plugins or extensions, and capture exclusions. It runs on Linux, macOS, and Windows through WSL2, with experimental native Windows support, and is distributed through Docker images and native release binaries.
Experiential is an open-source gateway and router for agent workflows from Experiential Labs. Its `exp` CLI provides hosted, bring-your-own-key, local, and custom models through OpenAI-compatible and Anthropic Messages APIs, with model aliases, access controls, use-case restrictions, and spending limits for users and agents. It can persist provider connections and configuration locally, expose API routes on loopback, and load a fitted project router as an OpenAI client through its Python interface. It collects OpenTelemetry traces from agent traffic to build simulations and optimize routing for quality, speed, and cost, and supports harness optimization, endpoint serving, model distillation, and fine-tuning an owned open-source model through Tinker. The hosted gateway is available at `api.experientiallabs.ai`; anonymous aggregate PostHog telemetry is enabled by default locally and can be disabled.
Doop is an open-source multiplayer design canvas where people and AI agents create and edit designs together. Each canvas contains frames that render real HTML in sandboxed iframes; humans edit in the browser, while agents connect through the built-in Model Context Protocol (MCP) server and can create frames, stream HTML in chunks, inspect screenshots, and revise designs. The app synchronizes cursors, presence, frame edits, agent status, comments, tasks, and activity over WebSocket rooms, and includes a server-side Doop Agent that can process queued cards, mentions, and feedback through specialist roles. Canvases are private by default, with email invitations or optional link sharing, and agents inherit the access of the user who authenticates them. Doop also provides design-memory features for exemplar frames, decisions, and proposed style rules, and can be self-hosted with Docker Compose or Bun using embedded Postgres through PGlite.
ego lite is a macOS browser from Citro Labs designed for AI-agent browser automation alongside a user's normal browsing. It gives each agent or task an isolated Space within the same browser, allowing multiple tasks to run in parallel without taking over the user's tabs; users can observe, take over, or stop an agent's Space. Through the ego-browser skill, agents such as Claude Code, Codex, Cursor, or custom agents can call in-page JavaScript tools including snapshot, fill, click, wait, navigate, and capture; an agent can compose several operations into one JavaScript execution rather than repeatedly issuing CLI commands. During setup, optional Chrome-data migration can transfer existing logins, cookies, extensions, and bookmarks, while browsing data remains on the user's device. The browser is distributed as a separate free download, the repository is MIT-licensed, and Windows and Linux support are listed as planned.
SwarmForge is a local, tmux-based orchestration platform for coordinating multiple AI agents across Git worktrees. It reads a project-local configuration that assigns roles, agent backends, worktrees, task or batch handling, and handoff propagation; launches each role in an isolated tmux session; and provides a browser-based pack cockpit for projects, tasks, approvals, clarifications, live status, agent-pane inspection, and teardown. Agents communicate through a daemon-delivered handoff protocol and helper scripts rather than direct tmux messages. The repository supplies two-pack, four-pack, and six-pack workflow templates with role prompts and constitution articles, while projects can define their own swarm topology. It runs locally with zsh, Git, tmux, Babashka, and at least one supported agent backend such as Claude, Codex, Copilot, or Grok; swarm state is kept in the working director
Rome is an agentic operating environment from Rome OS for collaboration between humans and AI agents. It provides manifests, typed actions, agents, skills, hooks, tools, workflows, memory, interfaces, policies, and persistent database-backed state in a guardrailed environment where agents can build applications, define standard operating procedures, and orchestrate workflows under human guidance. Rome supports one-off tasks, scheduled work, and long-running follow-through. Rome Apps combine a purpose-built web interface, agent reasoning, agent-owned collaborators, reusable workflows and skills, lifecycle hooks, typed actions, HTTP APIs, and persistent app-private databases or files into installable products. Apps are defined with an app.yaml manifest and use the @rome-os/app-runtime and @rome-os/app-web-sdk packages; Rome can generate and iterate on app or workflow source code from a plain-language request. The project can run locally through Docker or be accessed through Rome Cloud, which the repository describes as a private preview environment.
Proliferate is an open-source AI IDE for running coding agents such as Claude Code, Codex, OpenCode, Cursor, and Grok through their native harnesses. It runs agents in parallel within one workspace, giving each task an isolated Git branch and worktree along with its own terminal, conversation, and review state. Agents can delegate scoped work to subagents, while MCPs, skills, Computer Use, Browser Use, and custom tools can be configured once and shared across agents. Its workflow system supports recurring and event-driven runs such as review passes, alert triage, and dependency updates. The desktop application can use a local runtime or connect to a control plane that runs locally or in the cloud. The control plane is self-hostable through Docker, AWS, GCP, Azure, Kubernetes, or air-gapped deployments. The repository lists Rust, Node.js, and pnpm as source-build requirements and is licensed under AGPL-3.0.
MiniMind is an open-source tiny large-language-model project and end-to-end training tutorial developed by Jingyao Gong. Its main dense model is approximately 64M parameters, and the repository provides the model architecture, tokenizer, datasets, inference code, and training pipeline. The pipeline covers pretraining, supervised fine-tuning, hand-written LoRA, DPO, PPO, GRPO, CISPO, model distillation, tool calling, adaptive thinking, and agentic reinforcement learning. Core algorithms are implemented directly with native PyTorch rather than relying on high-level abstractions from third-party training libraries. Its agentic reinforcement-learning path performs multi-turn rollouts, executes generated tool calls, appends tool observations to the context, calculates trajectory-level rewards, and updates the policy; rollout can use local PyTorch generation or an SGLang server. MiniMind supports dense and mixture-of-experts variants, single- and multi-GPU training, YaRN-based RoPE length extrapolation, Transformers-format models, and inference through llama.cpp, vLLM, or Ollama. The repository also includes a Streamlit chat interface and a lightweight OpenAI-compatible API server with tool-call and reasoning fields. It is released under the Apache License 2.0.
Codewhale is an open-source coding agent for the terminal, built in Rust and independently maintained. It reads repositories, edits files, runs commands, inspects results, and works toward user-defined goals. It connects to hosted providers or local models through Ollama, vLLM, or SGLang, supports switching providers and models during a session, and can run interactively in a terminal UI or non-interactively with the `exec` command. Its control mechanisms include read-only planning, Ask, Auto-Review, and Full Access approval modes; `/undo` reverts the last turn and `/restore` returns the workspace to an earlier snapshot. It also supports saved sessions, durable goals, reviewable workflows, agent coordination, MCP servers, skills, hooks, and configurable agent roles. The project runs on the user's machine with the access granted to it, with optional operating-system sandboxing where supported, and is distributed under the MIT license.
TrustMeBro is a Go command-interception tool for controlled red-team testing of coding agents such as Codex, Claude Code, and pi. It uses PATH shims to intercept configured command-line tools without requiring a plugin, hook, or MCP integration; rules can spoof generated or fixed output, rewrite stdout from a real command while preserving stderr and its exit status, pass through to the real binary, or reject the call. Each decision is recorded in a timestamped JSONL audit log. Rules match command names, domains, DNS record types, argument globs, and regular expressions. The bundled DNS generators support dig, nslookup, and host, while custom shims can use fixed output, exit codes, and standard streams. On Linux, lab mode uses Bubblewrap to shadow PATH lookups and discovered absolute paths so an agent cannot bypass interception merely by invoking a resolved system binary. TrustMeBro is distributed as a single MIT-licensed Go binary with installation, configuration validation, status, rule-listing, and uninstall commands. Lab mode requires Linux and Bubblewrap and is explicitly an interception namespace rather than a security sandbox: it reuses the host filesystem, workspace, network, environment, and agent credentials. Outside lab mode, absolute paths, changed PATH environments, and in-process DNS clients can bypass command shims.
HexStellar is an agent-first computational platform whose Cortex service executes structured optimization, decision, scientific-computing, and verification requests through a Python CLI and API. An agent submits a JSON formulation for problems such as QUBO/Ising optimization, maximum cut, traveling-salesperson routing, facility assignment, mixed-integer optimization, selection, ranking, scheduling, coloring, and business-rule feasibility; the managed service returns a structured result with execution metadata, a receipt, and an assurance label distinguishing certified optima, heuristics, operations, and abstentions. The CLI also provides free validation, estimation, service re-checks, local witness recomputation for supported families, reproducible seeds and model versions, batch and compressed-binary transport, and an MCP server over standard input/output, with read-only mode for free analysis and verification tools. The public package is a zero-dependency Python thin client: the proprietary solver runs on HexStellar-managed infrastructure rather than inside the package. A separate enterprise runtime is licensed for compatible customer-controlled compute paths under NDA; it has no public runtime download in version 1.0.
Editable Visual Design is an open-source, coding-agent-driven toolkit for creating editable visual artifacts from prompts. A persistent coding agent interprets a brief, plans a composition, generates assets, implements the design in semantic HTML, renders and observes the result, and applies repairs. An image model supplies visual direction for composition, hierarchy, color, and spatial relationships, while the delivered artifact rebuilds typography and layout in HTML rather than shipping reference pixels. The resulting artifact contains real text, independent assets, selectable and movable layers, a visual editor, rendered PNG output, an animated layer breakdown, and a replayable creation process. Deterministic checks cover the canvas, fonts, layer contracts, rendering, and editor round trips. The repository distributes the workflow as two Codex skills, including editable-design for fixed-canvas designs and a separate html-to-pptx skill for converting compatible HTML designs into editable presentations.
Magnitude is an open-source local inference server and CLI for running language models with AI agent harnesses. It profiles a machine's chip, memory, and bandwidth, recommends compatible models, downloads the selected models, tunes inference settings such as speculative decoding and concurrency, and runs models on demand. Models are loaded when needed and unloaded when idle or when memory is constrained; prompts, files, and models remain on the local machine, allowing offline operation after setup. It integrates with Pi, OpenCode, Hermes, OpenClaw, Codex, Claude Code, Oh My Pi, and Cline, and also provides a built-in harness. Magnitude supports macOS and Linux, with Windows support through WSL, and is licensed under Apache 2.0.
Chrome DevTools for agents (chrome-devtools-mcp) is an MCP server from the Chrome DevTools project that lets coding agents control and inspect a live Google Chrome or Chrome for Testing browser. It uses Puppeteer for browser automation, including navigation and actions that wait for results, and exposes DevTools capabilities for recording and inspecting performance traces and insights, analyzing network requests, taking screenshots, and inspecting browser console messages with source-mapped stack traces. A CLI is also provided for use without MCP, with configuration options including headless, isolated, slim, concurrent-session, persistent-profile, WebSocket, and Android-debugging modes. It requires Node.js LTS, a current stable Chrome version or newer, and npm. Browser contents are exposed to MCP clients; performance tools may query the Google CrUX API, and usage statistics and update checks are enabled by default with an opt-out flag.
Monocolor Editorial Print is an agent skill for generating one-ink or controlled two-ink editorial images for posters, zines, portraits, packaging, and visual field notes. It accepts a theme, phrase, object, article idea, or supplied photograph and produces a raster image when image-generation tools are available, the exact production prompt, and a short recipe describing the print mode, palette, layout, typography, process, and originality changes. The skill identifies the subject and intent, selects a layout family, assigns one or two ink plates, composes the page with visible paper and an asymmetric grid, and generates and inspects the result. Its visual system uses adaptive white, gray, or beige substrates; halftone, risograph grain, cyanotype exposure, or photocopy breakup; responsive typography; and controlled negative space. Without image generation, it returns the prompt and states the limitation.
Sierra is an AI agent platform for businesses. Its agents use tool calling to handle customer support, sales, and other pre-sale and post-sale workflows, with an outcome-based pricing model.
HyperFrames is an open-source framework for turning HTML, CSS, media, and seekable animations into deterministic MP4 videos. It can be used locally through a CLI, by AI coding agents through skills, or as a rendering core for hosted authoring workflows. Compositions are defined as HTML with data attributes for timing, tracks, media, and sub-compositions. The renderer seeks each frame in headless Chrome, uses animation adapters such as GSAP, CSS, Lottie, Three.js, Anime.js, or WAAPI, and encodes the result with FFmpeg; its toolchain includes preview, linting, inspection, local rendering, browser-based editing, reusable catalog components, and AWS Lambda rendering. The project requires Node.js 22 or newer and FFmpeg, does not require React or a build step, and is licensed under Apache 2.0. Its agent skills support workflows including product videos, explainers, pull-request videos, captions, motion graphics, slideshows, music-driven videos, and general compositions.
Ponytail is a rule set and plugin for AI coding agents that directs them to implement the smallest working solution. Its decision ladder skips speculative requirements, reuses code already in the repository, prefers the standard library and native platform features, avoids adding dependencies, and then chooses the shortest implementation that works. The project says that validation, error handling, security, and accessibility are not simplified away. It provides chat commands for changing enforcement intensity, reviewing the current diff for over-engineering, auditing an entire repository for bloat, recording deferred shortcuts in a debt ledger, and viewing benchmark results. It can be installed across multiple coding-agent environments, including Claude Code, Codex, Copilot CLI, Gemini CLI, and Pi; the page also lists support for other agents. The project reports lower code volume, token use, cost, and execution time in benchmarked Claude Code sessions editing a FastAPI and React repository, while noting that results vary by task and model.
DeskcommCRM is an open-source, self-hosted CRM and AI sales operating system for businesses that sell through WhatsApp and other chat channels. It combines a multi-tenant CRM and sales pipeline with inbox, Kanban pipelines, contacts, team governance, audit logs, LGPD features, webhooks, automations, scheduling, and human takeover capabilities, and supports WhatsApp through WAHA QR connections or the official Meta Cloud API. Its AI agents use tenant-specific RAG, organizational memory, executable skills, intent routing, sentiment analysis, follow-ups, and audited handoff to human attendants. Agents can operate CRM records such as leads and funnel stages, while the CRM exposes an internal MCP interface for agent operations. Tenants can receive leads through public webhook endpoints and process event-driven QUANDO/SE/ENTÃO rules through an event-log queue drained by scheduled workers. The application is built with Next.js, TypeScript, and Supabase/Postgres.
PR Lens is a pull-request visualization tool by Coldtea that generates animated architecture and data-flow diagrams and posts them inside GitHub pull requests. It maps a change's components and call paths, uses green for new elements, amber for changed elements, and red for removed elements, and provides step-by-step walkthroughs, nested diagrams, and interactive canvases with pan, zoom, and light or dark themes. It is available as a GitHub App, GitHub Action, CLI, or coding-agent skill. The CLI analyzes a diff against a merge base, produces a graph document, renders theme-paired SVGs, validates documents against a schema, and can compose the pull-request comment. The GitHub Action can use Gemini, OpenAI, or an OpenAI-compatible endpoint; the agent skill lets a coding agent generate and attach the diagrams. Repository configuration in .github/pr-lens.yml supports renames, exclusions, lane pins, and groupings. The repository documents Node 20.11+ and pnpm 10 requirements and is licensed under the MIT License.
OKF Agent Memory is a Git-native persistent memory layer for AI coding agents, developed as a pure Go CLI and library. It stores project knowledge as plain Markdown files with YAML front matter in a repository, following the vendor-neutral Open Knowledge Format (OKF) v0.2 rather than relying on an external vector database. The tooling parses and validates OKF bundles, builds an in-memory BM25 index for local lexical search, and provides progressive disclosure through hierarchical index files and link graphs. Its search-before-write workflow queries existing concepts before creating new ones; concepts can include provenance, trust tiers, lifecycle metadata, and code references for linking knowledge to source files. The standalone executable also supports creating and updating concepts, bootstrapping the memory structure into a project, and running an embedded Model Context Protocol (MCP) server over stdio for agent platforms. The repository reports sub-300-microsecond concept search and approximately 4-millisecond graph validation for its benchmark cases, with no external databases or API costs for retrieval. It is distributed under the MIT License.
Bot Crossing is a local web application that visualizes coding-agent threads as an astronaut colony. It reads session records from installed agent harnesses on the user's machine, maps repositories to persistent hex zones, and represents sessions as astronauts whose behavior reflects states such as running, waiting, errored, merged, archived, or inactive. Selecting an astronaut or repository opens its associated thread through the owning harness, while the application can also start sessions, reveal folders, mark threads viewed, and archive them. The application uses per-harness adapters to scan local session files and merge them into a common thread model. It currently documents support for Claude Code, Codex, and Cursor, with adapters for other harnesses able to be added under `server/harnesses/`. Astronaut navigation uses a rasterized navigation grid, A* routing, string-pulling, collision handling, and crowd separation. The browser renders the colony with Three.js techniques including instanced GPU-skinned astronauts, shader-based construction progress, procedural terrain and surfaces, and configurable planets, lighting, and quality settings. Bot Crossing runs locally through a Vite development server or a built Node server, binds to loopback by default, and stores the colony layout in `data/colony.json`. It does not upload session data or use an account; it reads harness records and writes only the colony state plus the documented archive field. The repository requires Node 22.13 or newer, supports macOS, Linux, and Windows, and is licensed under MIT. Bundled Kay Lousberg assets are separately covered by CC0, while bundled Material Design Icons use Apache-2.0.
anything2explainer is a Claude Code and Codex skill for producing narrated explainer videos from a topic or document. It outputs a 1280×720 H.264 MP4 in Chinese or English, with synchronized TTS voiceover, word-aligned subtitles, chapter cards, a top HUD, and a chapter progress bar. Every frame is drawn as code with Remotion, React, and TypeScript rather than generated video or stock footage. Its pipeline researches the subject and records sources, writes the narration, generates voiceover and a frame-accurate timeline, storyboards each shot, dispatches parallel agents to build Remotion components, renders the film, and runs quantitative frame metrics plus chapter-level quality-control and fix passes. The repository includes a compilable Remotion template, visual primitives, style and motion specifications, scripts for voiceover, storyboarding, rendering and QC, and a complete reference film with its research and production records. It is not a standalone CLI; it is a skill and production method intended for AI coding agents. The toolkit is licensed under PolyForm Noncommercial 1.0.0: noncommercial use is free, while commercial use requires prior authorization. The videos produced with it are described as belonging to their creators. It renders through headless Chromium on the CPU, supports landscape output rather than 9:16 video, and provides two backdrops within its specified visual style.
WeKnora is an open-source, LLM-powered knowledge platform from Tencent for turning documents into queryable knowledge bases, retrieval-augmented Q&A, autonomous reasoning workflows, and self-maintaining Markdown wikis. It supports RAG-based quick Q&A and a ReAct agent that orchestrates retrieval, MCP tools, sandbox skills, and web search for multi-step tasks. Its Wiki Mode distills source documents into structured, interlinked Markdown pages with an interactive knowledge graph, manual editing, revision history, line-level diffs, and rollback. The platform ingests formats including PDF, Word, Markdown, HTML, images, spreadsheets, presentations, and XMind, and can synchronize sources such as Feishu, GitLab, Tencent IMA, Notion, Yuque, and RSS. Its modular pipeline supports interchangeable parsers, LLMs, embedding providers, vector databases, and storage backends, with dense, sparse, hybrid, parent-child, and graph-based retrieval strategies. WeKnora provides a web interface, REST API, command-line client, MCP server, website embed widget, and integrations with messaging channels. It can be deployed locally, with Docker, or on Kubernetes, including private and offline deployments. The repository states that it is licensed under the MIT License and supports workspace RBAC, scoped API keys, audit logs, and Langfuse-based observability.
SoL-Pi is an open-source standalone extension for the Pi coding agent, developed and maintained by NVIDIA. It packages four opt-in efficiency mechanisms: Action Fusion runs a follow-up validation command in the same edit or write call; ObservationPack replaces repeated large tool results with stable handles that support exact paged recall; the Evidence-Preserving Reducer condenses diagnostic logs into receipts only when retained quotations match archived source material; and Online Context Compact marks completed plan steps for Pi's native compaction when economic and context-window checks allow it. The extension operates through Pi's public APIs without patching or vendoring Pi, leaves the mechanisms disabled by default, and preserves original observations locally. It requires Node.js 22.19 or newer and is released under the MIT License.
An open-source Codex configuration that uses Astra as the root orchestrator and independent reviewer, with Luna-based subagents for exploration, implementation, testing, and research. It provides separate Pro and Plus profiles, TOML role configurations, an Astra orchestrator skill, project-level AGENTS.md instructions, and shell and PowerShell installers that copy the selected configuration into a target repository. The profiles set model, reasoning-effort, approval, sandbox, and concurrent-thread settings, while named role files can override the defaults. The repository also includes guides for orchestration patterns, plan-specific setup, iteration, and token-usage reporting from Codex session logs. It is licensed under Apache License 2.0.
Birdview is an open-source developer tool that makes AI coding agents map a project's architecture before editing. Its Birdview workflow defines modules, responsibilities, file ownership, evidence, relationships, and layout in an architecture JSON file; an agent then declares planned task scope, targets, files, lifecycle phases, and verification records against that map in an activity JSONL stream. Validators check the schemas and cross-record rules before a renderer produces a standalone interactive HTML view with architecture, changes, comparison, module evidence, and activity-history views. Birdview supports automatic or on-demand activation through project-level agent guidance and includes Node.js scripts, JSON Schemas, example maps, and tests. The generated output has no server or network dependency, but the v0.1 implementation is file-based: activity is agent-declared rather than automatically observed, and updates require regenerating the HTML. It is MIT-licensed and is not published to npm.
Coder is a self-hosted platform for cloud development environments and AI coding agents. It defines workspaces with Terraform and can provision them on EC2 virtual machines, Kubernetes pods, Docker containers, and other infrastructure, connecting users through a secure WireGuard tunnel and automatically shutting down idle resources. Coder Agents runs a native AI coding-agent loop in the control plane on the operator's infrastructure. It supports models from Anthropic, OpenAI, Google, Amazon Bedrock, and self-hosted providers without placing LLM credentials in workspaces, while providing centralized model governance, cost tracking, identity on actions, and audit logging. Workspaces can be accessed through existing IDEs including VS Code and JetBrains products.
@shadcn/lint is an agent-first linter for Tailwind v4 design systems. It lets teams define component and theme rules that coding agents can verify through ESLint or Oxlint, reporting violations with suggested fixes drawn from existing components, variants, and theme values. Its rules include preventing component restyling, raw colors, arbitrary values, inline styles, unknown Tailwind classes, and dynamic classes the linter cannot read; custom contracts, messages, placeholders, component-import settings, and shared configuration are supported. It can be used with custom Tailwind components and does not require shadcn/ui. The package requires Node.js 20.19 or later, with ESLint 9.30 or later or Oxlint 1.80 or later, and is licensed under MIT.
Pizza Bot is a local-first inbox for long-running AI-agent work, developed at Amazon. It lets users start or schedule tasks, switch conversations, and return to completed work in an Unread queue or approval requests in an Action queue. Its stateful DeepAgents/LangGraph runtime checkpoints runs so they can continue after a client disconnects; cron and webhook triggers can also start work. Electron, browser, and terminal clients communicate with an api-server over HTTP/SSE, while skills provide tool-scoped subagents and MCP servers extend the system. The project supports model providers including Amazon Bedrock, Anthropic, Google Gemini, OpenAI, OpenRouter, and Ollama. It stores application state locally, requires explicit folder permissions for local file access, and is distributed under the Apache 2.0 license with desktop installers for macOS, Windows, and Linux.
AgentVerse OS is a personal cloud operating system for a developer and their AI agents, installed on an Ubuntu server and accessed through a browser from a laptop, tablet, or phone. It provides a windowed desktop, isolated project workspaces, browser-based VS Code and a terminal, and supports Claude Code and Codex agents whose work remains on the server. Each project runs in an isolated Incus container with Docker inside, its own network and access gate. A Rust core coordinates projects, workspaces, capabilities, applications, backups, and updates; Coder controls the workspaces, Komodo deploys application stacks, Caddy provides the entry points, and Tailscale supplies private access and certificates. Projects request capabilities such as S3 storage, an LLM gateway, or notifications, which the core connects to provider networks and exposes through environment variables. The system includes a store combining catalogs from Runtipi, Coolify, and Umbrel, with guided installation, logs, snapshots, rollback, and application updates. It also supports ZFS snapshots, restic backups, an embedded Svelte desktop PWA, and one-command installation from a release package or source. The project is in alpha, is designed for one person, has no user accounts or permissions yet, and requires a clean Ubuntu installation and a Tailscale account. The repository is licensed under Apache-2.0; store applications retain their own licenses.
Databricks is a unified platform for data, analytics, and AI. It supports ETL, data warehousing, governance, and AI workflows through a data-centric platform. The videos describe its use for security detection, organizational ontologies, agents, and internal enterprise AI workflows.
Splash is a local inference engine for Apple silicon developed by Inco AI. It serves selected language models to coding agents and clients compatible with the OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages APIs, with streaming, tool calls, JSON Schema output, image input, and inline PDF support. Its runtime uses model-specific fused Metal kernels, weights packed for those kernels, a dedicated DFlash 2 draft model for speculative decoding, and a startup-computed memory plan for context, KV cache, and batching. The served model packages include the target model and its draft model; plain MLX or Transformers checkpoints are not supported. Splash runs locally on macOS, binds to a local HTTP server by default, and can be installed through Homebrew. The project is licensed under Apache-2.0, while model weights retain their own licenses.
Hindsight is an agent memory system developed by Vectorize.io for storing, retrieving, and synthesizing long-term memories for AI agents. It organizes memories into world facts, experiences, observations, and mental models within isolated memory banks, with support for multilingual data and optional per-bank scanning for secrets and personally identifiable information. Its retain operation uses an LLM to extract facts, entities, relationships, and temporal data, then normalizes them into searchable representations. Recall combines semantic vector search, BM25 keyword matching, entity/temporal/causal graph links, and time-range filtering, merging results with reciprocal-rank fusion and cross-encoder reranking. Reflect performs deeper analysis of stored memories to form connections and answer questions requiring more than retrieval. Mental models and knowledge pages provide continuously updated answers or documents derived from a bank's memories. Hindsight can run as a Docker service, Python package, embedded database, Kubernetes deployment, or hosted Hindsight Cloud service. It provides Python, Node.js, Go, CLI, and REST clients, an OpenAI-compatible LLM wrapper, integrations for agent frameworks and coding agents, and a built-in Model Context Protocol server. Self-hosted storage uses PostgreSQL with pgvector or Oracle AI Database 23ai; the project is MIT-licensed.
OpenMuse is a personal-agent application built by CopilotKit for iOS, Android, and web. It combines a persistent Chromium browser with an optional isolated Linux container, file and PDF handling, visible task plans, action reviews, and browser or terminal takeover so a person can inspect or continue the agent's work. It also provides Gmail and Google Calendar adapters with review required for sends and calendar changes. The application runs an API, durable task worker, and browser worker. Tasks use stored plans, progress, approvals, pauses, retries, and SQL leases; the browser worker maintains persistent Chromium profiles, while the optional non-root Linux container provides a retained workspace volume with bounded commands and no host-directory mounts or credentials. The interface is built with CopilotKit headless chat and AG-UI events, with inline email, browser, PDF, plan, and finance results. The repository describes OpenMuse as an alpha for self-hosting and building on, with model and Google-account configuration required for live agent and mail/calendar workflows. It is MIT licensed; CopilotKit Intelligence is a separate required service for rich conversation persistence and is not included under the repository's license.
Unreal Agent is an async-first agent harness from Unreal Labs. Its library and command-line executables coordinate persisted agent sessions, LLM turns, tool calls, and asynchronous operations. Inputs carry caller-supplied globally unique IDs for deduplication; sessions store append-only history that can be recovered or forked; and tool translators validate model-produced calls and convert them into serializable operations whose execution state is tracked separately. The harness includes a session inbox, coordinator, session store, context builder, LLM adapter, tool registry, tool translators, and an operation manager. Session and operation data are versioned and serializable, allowing operations to be dispatched to alternative or remote runtimes; unsupported session versions produce an explicit resume error. The repository contains the harness library, executables, and benchmark runners.
Z.ai's coding agent harness and AI programming workspace, offered through a desktop application, browser interface, and terminal agent. Its repository contains the client, backend services, shared React UI, Agent CLI, and runtime; the desktop client uses Electron, while the web and server components communicate through HTTP and WebSocket services. It supports remote project connections over SSH and WSL. The standalone command-line distribution combines a terminal UI, web server, and agent, and can run locally without Electron; the same command starts either the terminal interface or a browser-accessible web interface.
CLM is an AI decision-making model and Python service that selects among candidate actions by embedding a state and each action separately, then scoring their alignment instead of generating a textual response. It is trained with bidirectional InfoNCE: matched state-action pairs are pulled together while incorrect or hard-negative actions are pushed apart. At deployment, cached state and action embeddings are scored with a projection head, enabling typed decisions such as binary judgments, choices, and ordered scores, as well as ranking candidate answers, tools, trajectories, or next moves. The repository provides CLM-8B through a TypeSafe-compatible HTTP API and a local Python engine. It runs a Qwen3-8B pooling encoder through vLLM, exposes endpoints including `/v1/systemone` and `/v1/rank`, and includes a browser playground, embedding and action caches, checkpoint hot-reloading, and scripts for fine-tuning projection heads on typed decisions or agent trajectories. The reference head can run on CPU or GPU, while the encoder is served separately; states longer than 2,048 tokens are truncated by default unless the limits are raised together. The project is released under the Apache 2.0 License, and the repository's CLM-8B weights are also released under Apache 2.0 on Hugging Face.
QMD is an on-device command-line search engine for Markdown notes, meeting transcripts, documentation, knowledge bases, and other organized information. It combines BM25 full-text search, vector semantic search, and LLM reranking locally through node-llama-cpp and GGUF models. Its hybrid query pipeline expands the original query into lexical, vector, and HyDE variants, routes them to keyword or vector search, combines the results with Reciprocal Rank Fusion, and applies an LLM reranker to produce final ranked results. Collections can be indexed and enriched with hierarchical context; documents can be retrieved individually or in batches, and JSON and file-oriented output formats support agent workflows. QMD also exposes query, retrieval, batch retrieval, and index-status operations through an MCP server.
Duet is an AI agent-development tool that generates agent operating procedures, integrations, tools, tests, and simulations from customer transcripts and documentation.
An AI agent for reviewing large volumes of production conversations, identifying trends and weak topics, creating model variants, and drafting improvements for a primary conversational agent. It is associated with Decagon's conversational AI platform.
LlamaIndex is an open-source data framework and developer platform (originally GPT-Index) that provides connectors, indexing structures, and retrieval utilities to connect documents and external data to large language models. It is maintained by the LlamaIndex team and is used to build LLM-powered pipelines, agents, and document workflows.
AutoGen is an open-source framework from Microsoft for building and orchestrating agent-based workflows that use large language models. It provides components for defining agents, managing conversations and interactions, and integrating models and external tools.
BabyAGI is an experimental framework for building a self-building autonomous agent. Its core, the functionz framework, stores, manages, and executes functions from a database using a graph structure that tracks imports, dependent functions, and authentication secrets; it also supports automatic function loading and logging. A dashboard provides function management, updates, execution, and log viewing. The repository can be installed as a Python package and is intended for experimentation rather than production use. The original repository was archived in September 2024 and moved to a separate archive repository.
CrewAI is an open-source Python framework for building multi-agent workflows. Its Crews use autonomous, role-based agents that collaborate on tasks, while its Flows provide event-driven workflow control combining precise orchestration, individual LLM calls, and Crews. The project also offers CrewAI AMP Suite, a commercial control plane for managed deployment, observability, governance, security, enterprise support, and cloud or on-premise operation. The repository provides high-level abstractions and lower-level APIs, along with documentation, examples, installation guidance, and integrations for connecting agents to language models.
ChatDev is an open-source multi-agent framework from OpenBMB. Its original ChatDev 1.0 design models a virtual software company in which role-based agents such as a CEO, CTO, and programmer collaborate through specialized functional seminars to carry out software development tasks including design, coding, testing, and documentation. The current ChatDev 2.0, called DevAll, is a zero-code multi-agent orchestration platform. Users configure agents, workflows, and tasks to build and run customized multi-agent systems for scenarios such as software development, data visualization, 3D generation, and deep research.
Flowise is a visual, low-code platform for building AI agents and agentic workflows by connecting models, components, and third-party integration nodes through a graphical interface. Its monorepo contains a Node.js backend for API logic, a React frontend, component integrations, and autogenerated Swagger API documentation. It can be installed with npm, run with Docker, deployed self-hosted, or used through Flowise Cloud. The repository is archived and its source code is released under the Apache License 2.0.
Netic is an AI operations platform for essential-service companies that mediates customer interactions and deploys AI agents across voice, text, and websites. It applies operational rules, coordinates labor, and supports inbound, outbound, and analytical workflows.
Orgo is a provider of instant cloud computers designed for use by AI agents. It offers full Linux and Windows desktops accessible through an API, advertised as ready in under a second and controllable by autonomous software.
A workflow orchestration component of Microsoft's AutoGen framework for building directed agent workflows. It supports sequential and parallel steps, conditional branching, and loops.
An AI-agent development tool that compiles natural-language skills into structured Python programs. It applies schema, safety, security, and guardian-hook checks during compilation.
Conductor is an AI agent interface from Paper for creating Paper design frames, generating variations, and addressing design comments.
A development tool that automatically enforces the red-green-refactor test-driven development cycle for AI coding agents.
Probity is an open-source project by Nizar Selander that provides tooling to enforce test-driven development (TDD) guardrails for AI coding agents. It is designed to run and validate automated tests and checks against code produced by AI agents to ensure adherence to TDD workflows.
An AI voice-agent platform for building and deploying phone-based conversational agents. It supports agents that conduct automated interviews and other business conversations over telephone calls.
Custom GPTs is a feature of OpenAI's ChatGPT that lets users create and configure customized GPT instances with tailored instructions, behaviors, and integrations. It is provided by OpenAI to enable creation of conversational agents without writing code.
Phoenix is an open-source AI observability platform developed by Arize for experimenting with, evaluating, and troubleshooting LLM applications and agents. It traces application runtime with OpenTelemetry-based instrumentation, supports response and retrieval evaluations, and provides versioned datasets, experiment tracking, prompt management, and a playground for comparing models, adjusting parameters, and replaying traced calls. Phoenix also includes PXI, an AI engineering agent for debugging traces and iterating on prompts, plus a remote MCP server for querying traces, datasets, and experiments from MCP clients. It can run locally, in containers, through Kubernetes and Helm, or in the cloud, and is distributed through the `arize-phoenix` Python package, Conda, Docker images, and related TypeScript and Python packages.
Accio Work is an AI-driven platform from Accio that provides agentic teams to execute business tasks. The service offers built-in skills and connectors to integrate with external services and perform actions beyond conversational chat, aiming to automate workflows and run business operations.
Murmell is a cloud platform for running and coordinating AI coding agents (for example Codex, Claude, and Kimi). It provides a shared cloud sandbox for collaborative coding, real-time file-path locking to prevent merge conflicts, and tools to deploy from any terminal.