579 tools and products — trending open source, and what gets used in AI and other work.
Comp AI CRM is an open-source, self-hostable customer relationship management system for AI agents, developed by Comp AI and hosted by Try Comp AI. Its agent runs as an independent durable deployment on its own schedule and database-backed work queue rather than waiting for browser requests: it selects records to investigate, researches contacts and companies, spends a research budget, schedules follow-ups and rechecks, records observed evidence, and sends weak or ambiguous matches to a human instead of writing them directly to records. It supports durable sessions, contact and company records, an Agent tab for viewing work and answering questions, authored tools for reading CRM history, searching records, identifying contacts, researching people, enriching companies, recording facts and scheduling rechecks, and versioned Markdown skills. The agent uses file-based tools and Markdown skills on Vercel's eve durable-agent framework, while its queue leases due tasks with PostgreSQL row locking so concurrent workers claim disjoint work and expired leases release tasks from failed runs. A restricted shell sandbox provides bash, grep, glob and a workspace without network egress, database credentials or direct database access. Optional sources include mailbox history, company brand data, LinkedIn and Perplexity web research.
IP as Logo Skill is a compact Agent Skill in the open Agent Skills format that guides compatible AI agents in turning a product brief into highly simplified, rounded mascot-character concepts. It gathers product context, proposes three design directions, and after approval generates six independent full-resolution square candidates using one dominant silhouette of roughly four to seven large shapes, two mascot or IP colors, a named solid background color, thick rounded forms, and lower-left or lower-right corner emergence. Its default batch uses two variants per direction with a three-left, three-right composition split rather than a contact sheet. Familiar animals are the default subjects, while objects, machines, fantasy artifacts, and other unusual subjects require a clear product-related reason. The skill provides instructions and prompts rather than an image generator, can be installed with the Agent Skills CLI, and is intended for agents such as Codex, Coze, Doubao, YouMind, Manus, Gemini Apps, and Replit Agent when paired with a supported image model.
Composio is a developer platform for orchestrating just-in-time tool calls, secure delegated authentication, sandboxed execution environments, and parallel execution across integrations with 1,000+ applications. It is designed to let applications and AI agents invoke external tools safely and at scale.
LangFlow is an open-source, low-code visual builder for creating and running language-model pipelines, agent workflows, and retrieval-augmented generation (RAG) applications. The project is developed and maintained by the open-source community led by the GitHub user logaretm and integrates with language-model providers and tools such as LangChain.
Blotato is a social-media API, marketing, and multi-channel publishing platform that provides an MCP server for connecting marketing operating systems and AI agents or LLMs such as ChatGPT and Claude. It supports programmatic automation of social posts, including scheduling from Claude Code, as well as comment and direct-message management, content creation, and analytics.
Clay Studio is a self-hosted, browser-based team workspace for running and sharing local coding-agent sessions across projects. It connects to supported local runtimes such as Claude Code and Codex, allowing people and AI collaborators to share live sessions, hand off work, respond to permission requests, and retain project knowledge between conversations. The Clay Studio daemon runs on the user's machine and serves the workspace to a browser or mobile PWA. It stores sessions and knowledge on disk as portable JSONL and Markdown, and supports repositories, parallel sessions, Git worktrees, background workers, scheduled tasks, persistent AI collaborators called Mates, project instructions, file editing, diffs, terminals, MCP servers, and push notifications. The request path is browser to the Clay Studio daemon to the selected coding-agent runtime and its model provider; project traffic is not relayed through a Clay-hosted cloud.
MLflow is an open-source AI engineering platform for agents, large language models, and machine-learning models, developed in the MLflow repository. It provides experiment tracking for models, parameters, metrics, and evaluation results, along with production observability, evaluation, prompt versioning and optimization, and model lifecycle tools. Its agent and LLM observability captures application traces using OpenTelemetry and supports different LLM providers and agent frameworks; its AI Gateway provides an OpenAI-compatible interface for routing requests, managing rate limits and credentials, handling fallbacks, controlling costs, and applying guardrails. MLflow can be run as a server and accessed through Python, TypeScript/JavaScript, Java, and other programming languages, with integrations including OpenTelemetry and MCP.
Cloudflare Computer is an open-source library that provides AI agents with a virtual filesystem backed by a Cloudflare Durable Object. The Durable Object stores the authoritative state in SQLite, while the workspace exposes a single execution interface through `workspace.runtime.exec(source, { backend })`. It supports three execution backends: Container projects the SQLite state into a sandbox container through a FUSE mount and synchronizes changes over capnweb RPC; Isolate shell runs `just-bash` in a Dynamic Worker; and Isolate JavaScript runs an ECMAScript module in a fresh Dynamic Worker with structured inputs and results, durable relative imports, configured libraries, workspace-backed `node:fs/promises`, and trusted `ws:git` and `ws:artifacts` modules. Workspaces can register multiple backends under stable identifiers, connect to them lazily, or be used solely as a filesystem without an execution backend. The repository includes examples for container, Worker shell, Worker JavaScript, egress policies, MCP, agent workspaces, tutorials, artifacts, and assets. The package is marked preview-only: its APIs are unstable and the repository says it is intended for experiments, exploration, and prototypes rather than production use.
GenOffice is a free, open-source AI office suite from Genspark AI for macOS, Windows, and Linux. It consists of six Electron applications sharing an engine layer: Docs for .docx files, Sheets for .xlsx spreadsheets, Slides for .pptx presentations, PDF for viewing and editing PDFs, Markdown for plain Markdown files, and a shell application that hosts the editors. It opens and saves Microsoft Office formats, and includes light, dark, and system themes. Its AI panel supports document-aware, block-level edits with version snapshots and diffs; in spreadsheets, presentations, and PDFs it provides a tool-calling agent over document state. Built-in tools include web search, image search, image generation, and media analysis. Users can sign in through Genspark or supply their own keys for providers including Claude, OpenAI, Gemini, DeepSeek, Kimi, GLM, Qwen, Doubao, MiniMax, Grok, Mistral, and OpenRouter, as well as custom OpenAI-compatible endpoints and local servers. GenOffice Docs uses byte-preserving .docx editing in which only modified paragraphs are regenerated, with Word-compatible pagination, tracked changes, comments, styles, equations, and ink. GenOffice Sheets uses the open-source Univer core with in-house extensions and a Rust .xlsx import/export sidecar, plus charts, pivot tables, slicers, conditional formatting, and formula tracing. GenOffice Slides has an in-house .pptx parsing, rendering, and editing engine with masters, layouts, charts, cropping, ink, and text shaping. GenOffice PDF supports annotations, forms, outlines, stamps, signatures, page operations, printing, direct text reflow and image editing, and local conversion to editable Word, PowerPoint, or Excel files; scanned PDFs can use system OCR on macOS and Windows. GenOffice Markdown is a Tiptap block editor that saves headings, lists, tables, images, and code blocks back to plain Markdown. The suite is distributed under the Apache-2.0 license with installers for the three supported desktop platforms.
TencentDB Agent Memory is a self-hostable, team-level memory hub for AI agents. It extracts conversations and tasks into reusable Chat Memory and Skills, and converts documents and code into an LLM Wiki and CodeGraph. These assets can be reviewed, versioned, governed, shared, routed, and reused across agents, frameworks, and team members; existing documents, codebases, and agent sessions can also be imported to reduce cold-start work. The system provides a shared memory server and a proxy that preserves the agent protocol, so supported clients can use the same memory by pointing their base URL at the proxy without plugins, hooks, or an MCP server. The repository deploys memory-core, memory-hub, and the proxy together, with a local management panel and configuration for separate memory and proxy LLM parameters. Documented integrations include DeepSeek Harness, Claude Code, Codex, CodeBuddy, WorkBuddy, Hermes, and OpenClaw.
OfficeCLI is an open-source command-line Office suite developed by iOfficeAI for AI agents to create, read, edit, render, and automate Word (.docx), Excel (.xlsx), and PowerPoint (.pptx) files without a Microsoft Office installation or external dependencies. It is distributed as a single binary and provides commands for creating documents, adding, modifying, moving, copying, and removing elements, reading text and structure as plain text or JSON, and saving changes. Its built-in HTML rendering engine converts DOCX, XLSX, and PPTX files to HTML or PNG for a render-and-review workflow. The `watch` command provides a live browser preview that refreshes after document changes, while the tool can also analyze formatting and structural issues, evaluate Excel formulas, and install an agent skill for supported AI coding agents.
Waku Agent is an open-source, local-first personal assistant and AI-agent harness built by seanchen.io. It runs on a laptop through a terminal, local browser dashboard, voice input, or Telegram gateway, and is organized around four components: a harness for tool execution, an approximately 95-line plain-Python agent loop, memory, and evaluation/LLM operations. Its memory uses semantic, episodic, and procedural stores in a local SQLite database, with a gate that decides whether to retrieve or save memory and a pass that determines what to retain. The project includes deterministic tests alongside LLM-as-judge evaluation with a release gate. The dashboard displays message flow through the harness, including gate decisions, tool calls, loop iterations, memory updates, traces, costs, and latency; it also includes views for workflows, tools and MCP connectors, memory, and the SQLite state database. It can be installed with pip and exposes the `waku` command. The dashboard runs a local web server at `127.0.0.1:7777`, and the Telegram gateway starts when `TELEGRAM_BOT_TOKEN` is configured. Model providers are selected through a provider setting and API key, with support stated for Anthropic, OpenAI, Gemini, DeepSeek, MiniMax, Kimi, GLM, OpenRouter, OpenCode Zen, and OpenCode Go.
Fin is an AI customer-agent product from Intercom that automates support, sales, and e-commerce interactions across chat and voice channels. It is described as able to handle complex customer issues, update accounts, and process payments and refunds while managing end-to-end customer journeys inside Intercom's messaging platform. It is offered as part of Intercom's conversational support suite.
Docling is an open-source document-processing toolkit from the Docling project for preparing files for generative-AI applications. It parses formats including PDF, DOCX, PPTX, XLSX, HTML, EPUB, images, plain text, audio, and video, and represents the results in a unified DoclingDocument structure. For PDFs, it analyzes page layout, reading order, headings, tables, code, formulas, images, and scanned content through OCR. Audio and video inputs can be processed with automatic speech-recognition models; video parsing produces an ASR transcript and representative keyframes. Parsed content can be exported as Markdown, HTML, WebVTT, DocLang, DocTags, or lossless JSON. Docling supports local and air-gapped execution, a command-line interface, Python usage, an API server named docling-serve, and an MCP server for connecting agents. The project also provides integrations for LangChain, LlamaIndex, CrewAI, and Haystack. It is installable with pip and runs on macOS, Linux, and Windows on x86_64 and arm64 systems.
Open Science is an open-source, local-first, model-agnostic AI research workbench developed by AIPOCH for scientists and researchers. It runs on macOS, Windows, and Linux and supports computational and data-intensive research in fields including machine learning, statistics, life sciences, chemistry, materials science, physics, and environmental science. Users create projects and sessions, describe research goals in plain language, attach source files, select a model and approval mode, and inspect the agent’s tool activity. Scientific AI agents can read files, search the web, execute Python and R code, query scientific data sources, and produce reports, tables, figures, and other research artifacts. The workbench supports literature review, hypothesis development, code execution, data analysis, simulation, visualization, and related reproducible research workflows. Its first-run setup checks the environment, configures model-provider credentials, optionally prepares Python and R runtimes, and prepares an agent runtime such as Claude Code, OpenCode, or Codex; app-managed runtimes can be installed without Node.js, npm, or administrator privileges. Projects keep sessions, uploads, generated files, and preview state together. Conversations record agent answers and the commands, file reads, edits, searches, and connector calls behind them. Generated artifacts are stored as immutable, checksummed versions; their Provenance view can show producer code and execution history, referenced inputs, the observed environment inventory, the producing conversation branch, and version-scoped reviewer findings, marking unavailable evidence as unavailable rather than guessing.
Vibe-Trading is an open-source AI personal trading agent and quantitative-finance research workspace developed by HKUDS. It turns natural-language finance questions into runnable analysis and backtesting workflows by connecting an agent to market-data loaders, portfolio and backtesting engines, report generation, persistent memory, and multi-agent research teams across asset classes. Its quantitative and risk-analysis capabilities include strategy backtesting, Heston stochastic-volatility pricing, hierarchical risk parity, copulas, and market-microstructure estimators. The project provides API and MCP interfaces, broker and market-data connectors, portfolio-management and broker-authorized trading workflows, examples, documentation, a demo, and a Shadow Account for testing. It supports read-only account sources such as official IBKR MCP and opt-in Binance USD-M snapshots, while scheduling actions require explicit confirmation and live-order safeguards fail closed on contradictory or invalid data. Implemented as a Python project, it uses a connector onboarding system that stores connection secrets in the operating-system keyring and is distributed under an open-source license.
An open-source agent skill for redesigning GitHub README homepages around a repository's actual content. It reads the repository first, identifies the clearest value and supporting proof, and then derives a project-specific visual system rather than applying a shared template. In whole-README mode, it works across content, visual-system, and engineering layers: it removes repetition and internal jargon, moves proof toward the opening, derives typography, color, composition, and project-native motifs, and keeps assets GitHub-safe, accessible, searchable, and copyable. The skill separates visual and content layers by using SVG for editable heroes, section transitions, comparisons, diagrams, and identity while retaining maintainable Markdown for searchable body text. It supports hybrid SVG compositions with optional AI-generated elements, local previews, and an approval step before publishing. The repository documents examples used by eight public repositories, including project-specific heroes and real outputs for slide creation, UI reconstruction, icon generation, agent delegation, vehicle telemetry, interactive mapping, and a solo werewolf game.
text-to-cad is a library of agent skills for creating, inspecting, sourcing, slicing, previewing, and handing off CAD, CAE, CAM, robotics, and hardware-design artifacts from local project files. Its skills generate and edit CAD models from plain-language or image requests, primarily producing STEP files with optional STL, 3MF, and GLB exports; preview local CAD and robot files in a browser; source off-the-shelf STEP parts; and create DXF drawings from Python sources or CAD geometry. Additional skills write URDF robot structures, SRDF/MoveIt2 planning and collision data, and SDF simulator models and worlds; check DXF and STEP files for SendCutSend; measure mesh printability by wall thickness, overhangs, support volume, and build orientation; slice supported meshes into validated, printer-profiled FDM G-code using slicer command-line tools; and dry-run, upload, and cautiously start local Bambu Lab print jobs. An experimental implicit-CAD skill creates browser-native models with GLSL signed-distance fields and CAD Viewer raymarch rendering. The library is installed with the Skills CLI, including `npx skills add earthtojake/text-to-cad`, or through provider-native plugins for Codex, Claude Code, and Grok Build.
AI Job Search is an open-source, local job-application framework built around Claude Code or compatible agent tools. Users create a career profile, search and deduplicate job postings, evaluate and rank matches against structured fit criteria, and run `/apply` to produce tailored CVs and cover letters in LaTeX. The application pipeline uses a drafter–reviewer process: an agent evaluates the posting and drafts the materials, a second reviewer critiques them, and the workflow revises the output; `/interview` supports interview preparation, and optional salary benchmarking is included. The included portal-search skills target Danish services such as Jobindex, Jobnet, and Akademikernes Jobbank, while the profiling, fit-evaluation, and application workflow is described as language- and country-agnostic and adaptable to other job boards. It requires Python 3.10 or later, Bun for the job-search CLI tools, and a LaTeX distribution with `lualatex` and `xelatex`; an optional `pdftotext` installation supports the ATS parseability check for compiled CVs. The repository states that the project is independent of and unaffiliated with Anthropic or Claude Code.
An open-source AI agent skill for Claude Code, Codex, and similar coding agents that produces cinematic product, marketing, launch, and demo videos with Remotion. It provides shot recipe cards, motion previews, a reusable video template, and workflows for storyboarding, real page capture, animation, 2.5D camera moves, sound design, beat-synced cuts, and visual checks. The repository includes native Remotion components driven by normalized progress values, a gallery for browsing motion previews, and an optional JianYing project export that separates shot plates, captions, sound effects, and background music into editable tracks. It can be installed through the skills CLI, by cloning the repository, or by linking it into a Claude Code or Codex skills directory.
eve is an AI agent framework for building durable, structured, multi-agent projects from declarative configuration covering instructions, skills, tools, channels, schedules, permissions, and evaluations. Its agents can be developed within a single folder and run through chat surfaces such as Slack or the eve development TUI. Vercel uses eve as the foundation for a marketing-team template with one lead and five specialists: product marketing, content marketing, social media, SEO, and email. The lead loads shared brand context and user preferences, writes self-contained briefs, routes work one level deep, and returns deliverables produced in Notion, Typefully, or Resend; specialists research and edit their own work against written rubrics rather than spawning further agents. The template uses MCP connections for Notion, Typefully, and Resend, Vercel Blob for shared state and files, Vercel AI Gateway for model access, and Vercel Sandbox for reference files and shell commands. Irreversible actions—including email sends, deletes, scheduled social publishing, and Notion page moves—pause for human approval, while the available Resend tools are restricted to keep account administration out of reach. The project is implemented in strict ESM TypeScript and includes commands for local development, validation, type checking, discovery diagnostics, and deployment.
Impeccable is an open-source design skill for AI coding agents, developed by pbakaus. It provides a shared design vocabulary with 23 commands, including init, shape, critique, audit, polish, harden, animate, typeset, layout, and live. The init command gathers product and design context into PRODUCT.md and DESIGN.md files, while other commands review, plan, modify, or refine a frontend project. Its CLI and browser extension run 61 deterministic detector rules for common AI-generated frontend design problems without an LLM or API key; it also supports LLM-based critique checks. The live command provides browser-based visual iteration, and the package can be installed from a project root with npx impeccable install.
Ratel is an in-process context-engineering platform for AI agents. It catalogs tools, skills, and persistent facts, then searches the catalog on each turn and progressively discloses only the capabilities relevant to the request instead of placing every tool schema and instruction in the context window. Its retrieval supports BM25, semantic, and hybrid ranking without requiring a vector database. The project includes a Rust core, TypeScript and Python SDKs, an MCP server, and a CLI. Tools can be registered directly or ingested from an MCP server; skills can associate instructions with tools, while registered facts are re-injected when they are no longer fresh in the conversation. The repository describes the system as reducing token usage and mitigating tool overload.
SimpleEnglish is an open-source agent skill that makes large language models write technical documentation in ASD-STE100 Simplified Technical English, a controlled language used in aerospace. Its rules enforce short sentences, active voice, explicit instructions, simple tenses, and consistent terminology when rewriting READMEs, error messages, incident reports, runbooks, and release notes. The skill is distributed as a dependency-free folder for tools that support the Agent Skills standard, including Claude Code, Cursor, VS Code Copilot, OpenAI Codex, Gemini CLI, Goose, and OpenCode. It can also be installed as a Claude Code plugin and output style, or used by adding its prompt to a system prompt, AGENTS.md, or .cursorrules file. The repository is licensed under MIT.
Prime Agent is an open-source command-line coding and research agent for general and long-running tasks, developed by Prime Intellect. It combines recursive language-model workflows through an RLM harness with a persistent Python REPL, treating prompts as variables and invoking tools and recursive subagents programmatically. A continual harness stores supplemental prompts, memories, skill descriptions, and reusable subagent specifications as durable session state that can be refined through small, evidence-backed updates without changing the immutable base system prompt. The agent supports importable Python skills, parallel or background child agents, messaging between running agents, automatic context compaction, persistent goals, heartbeats, schedules, detached sessions, autonomous operation, and retained subagents.
Superpowers is an open-source agentic skills framework and software development methodology for coding agents. It begins by eliciting and presenting a software specification for approval, then produces an implementation plan emphasizing red/green test-driven development, YAGNI, and DRY. After approval, it uses a subagent-driven-development process in which agents implement engineering tasks, inspect and review the results, and continue according to the plan. It is distributed as a plugin for supported coding-agent harnesses, including Claude Code, Codex, Cursor, and others.
OpenEdit is an open-source, agent-driven video-editing pipeline from VEED. It has no graphical interface or timeline; an agent-agnostic skill and repository guide drive it through coding agents such as Claude Code, Codex, and Gemini. The pipeline can edit, cut, and reframe footage; create burned-in subtitles, motion graphics, charts, and visual elements; assemble slides, websites, stills, or generated media into video; capture web pages; and connect generation services or MCP servers when needed. Source footage is optional, and VEED Fabric can generate footage only with the user's approval. For captioning, the agent transcribes the video, designs the captions, renders the result, opens a video previewer, and accepts follow-up requests such as changing subtitle color, position, or emphasis. Transcription can use VEED, local offline WhisperX, or a user-supplied service; all providers must produce per-word timings, which are stored in a common transcript format. Caption styles are authored in HTML and CSS. The project includes VEED's closed-source but free-to-use HTML renderer, which does not require a headless browser; Chrome can be used as an alternative rendering backend. V1 primarily targets captions, while motion graphics, charts, and brand-book-matched styling are less exercised. OpenEdit supports Apple Silicon Macs and Windows x64 PCs. Intel Macs are unsupported, Linux support is planned, and Windows requires Git, Node, and ffmpeg. It can be installed from the repository or with `npx skills add veedstudio/open-edit`.
LoopX is an open-source, provider-neutral state kernel and local-first control plane for long-horizon AI agents and peer agent teams. It runs on top of agent harnesses such as Codex, Claude Code, Cursor, dsh, or a custom harness rather than replacing them, keeping objectives, gates, tasks, evidence, quotas, schedules, recovery state, and handoffs durable across bounded turns, sessions, tools, and agents. Its control layer makes semantic decisions about what happens next and supports governance, recovery, human-agent collaboration, and reviewable work. The accompanying personal agent workspace stores goals, attention, conversations, tasks, files, schedules, and recovery state locally across restarts; its supported browser/PWA dashboard can continue work across registered agent sessions and use typed previews, explicit confirmation, and receipts for protected changes.
Pi Web is an open-source local browser interface for the Pi coding agent, developed in the agegr/pi-web repository. It uses Pi’s local configuration and session files, allowing users to browse, resume, rename, export, delete, and branch project-grouped conversations; run agent turns; and inspect running state, context usage, costs, and compaction details. New sessions create independent session files, while “Edit from here” creates a branch within the current session. Its project workspace supports file browsing and uploads, Git diff inspection, automatic previews for source files, Markdown, images, audio, PDFs, and DOCX files, and Git worktree switching. Configuration panels manage provider logins and API keys, models and model tests, plugin packages, and skills. The interface supports English, Simplified Chinese, and Traditional Chinese, follows the browser language initially, and includes a language switcher. Pi Web is distributed through the `@agegr/pi-web` npm package, requires Node.js 22.19.0 or newer, and listens on `127.0.0.1` by default. Remote binding and HTTP Basic Authentication are available, but the documentation warns that Basic Auth does not encrypt credentials in transit and that the service should not be exposed over plain HTTP without a trusted reverse proxy or VPN. It reads Pi agent data from `~/.pi/agent` by default, shares Pi’s model, settings, and credential storage, and limits file browsing to known project or session roots rather than providing general filesystem access.
Kimi Code CLI is an AI coding agent developed by Moonshot AI that runs in a terminal. It reads and edits code, runs shell commands, searches files, fetches web pages, and selects subsequent actions based on the feedback from those operations. It works with Moonshot AI's Kimi models and can be configured with other compatible model providers. The tool is distributed as a single binary and provides an interactive terminal UI. It accepts video input, supports conversational configuration of Model Context Protocol (MCP) servers, and can install skills, MCP servers, and data sources from its marketplace or GitHub repositories. Built-in coder, explore, and plan subagents can work in isolated contexts, while lifecycle hooks can run local commands at selected points in a session. Kimi Code CLI also supports the Agent Client Protocol (ACP), allowing compatible editors and IDEs such as Zed and JetBrains to drive sessions through the `kimi acp` command. The repository documents installation for macOS, Linux, and Windows and provides OAuth or Moonshot AI Open Platform API-key login options.
numbat is an open-source endpoint security tool for monitoring AI-agent activity across supported desktop, CLI, IDE, and gateway agents. It combines local hooks and plugins, OTLP/HTTP logs, and on-disk session artifacts, normalizes live and stored activity into a common event model, and evaluates it locally with built-in, sequence-based, or custom YAML CEL rules. The tool can produce NDJSON events, findings, enforcement decisions, indicators, and scan summaries for alerting and forensic reconstruction, including read-only artifact scans, per-session timelines, and portable case bundles with SHA-256 manifests. Optional pre-action blocking is disabled by default and is limited to supported synchronous hooks and explicitly enforced rules. It is distributed as a single cgo-free binary for macOS, Linux, and Windows, with read-only inventory and scanning commands.
QM is a multiplayer agent harness for startups that operates through Slack and a web interface. It gives each employee and room an isolated scope with its own memory, files, keychain view, permissions, scheduled jobs, web apps, and durable sandbox, while supporting collaboration in channels, group messages, and projects. Shared skills can be granted by scope, promoted by administrators, or imported from Git repositories; background work can run through crons, watches, and inbound webhooks, and internal apps can be published to selected users. A headless TypeScript core runs directly on Node with Fastify and handles identity, policy, scheduling, persistence, and the agent loop. Deployments can select harnesses and models including Pi, OpenCode, Codex, and Claude Code. PostgreSQL stores sessions, memory, queues, and other durable state, while a fixed tool surface includes an execute tool that runs commands in each scope's isolated, persistent sandbox. Slack is an optional in-process Bolt plugin; the web UI, admin panel, and public portal are optional HTTP API plugins built with Vite and Lit. Each deployment keeps organization-specific configuration, tools, skills, sandbox images, and infrastructure in a deployment directory validated and deployed by the qm CLI. Administrators can set organization-wide configuration, available harnesses and models, and a security posture. Strict mode pauses harness tool calls for human approval, Auto mode screens provenance-labelled external data and tool results with a classifier, and Dangerous mode disables content screening and pauses; a predeclared command policy with approvals and hard denials for operations such as recursive deletion or destructive SQL applies in every posture. Deployments run in the operator's own cloud account and are initialized from the @yc-software/qm package without requiring a source checkout; the project documents its threat model, operator assumptions, and known limitations in SECURITY.md.
Bindwidth is a browser-based calculator for sizing on-premises LLM inference infrastructure and estimating total cost of ownership. It evaluates three constraints for a resident text model—KV-cache memory, combined prefill and decode serving capacity, and the runtime session ceiling—and identifies which constraint binds for a workload. The tool accounts for interactive users and autonomous agents as different load types, then compares owned hardware, eligible sovereign rentals, and enterprise subscriptions with per-token APIs for agents. It distinguishes measured from estimated hardware and model data through confidence levels and profile-specific overrides, flags domain and model-capability limits, and exports a decision record as Markdown or the full scenario as JSON. The repository describes it as a directional sensitivity estimator rather than a procurement quote. It is a frontend-only application with no build step, server, database, account, or telemetry; calculations run in the browser and entered data is not transmitted.
Octop is an open-source, self-hosted AI assistant platform for households and small teams. It runs as a single process, storing conversations, workspaces, credentials, and shared state in a SQLite database under ~/.octop/, while serving a web dashboard, CLI, chat integrations, and cron automation. Users can switch among specialized personal agents through its multi-agent architecture. Built on the Harness stack, Octop combines an agent runtime for model routing, tools, skills, and conversation checkpoints with a gateway that normalizes messages from supported chat platforms into one processing pipeline. It also provides a built-in expert library, portable workspace memory, OAuth and MCP connectors, ACP integration for IDE and terminal workflows, browser automation, terminal-assisted command execution, and remote desktop access. The project uses FastAPI and uvicorn, React with TypeScript and Vite, SQLite through aiosqlite, and APScheduler. Its security features include JWT-based multi-user isolation, tool approval, shell-command guardrails, and PII redaction; supported storage backends include local disk, Docker containers, PostgreSQL, and COS/S3.
Phone Harness is an open-source harness that lets AI agents such as Claude Code, Codex, or other LLMs control a real iPhone or Android phone without a jailbreak, injected app, Xcode, WebDriverAgent, or on-device installation. It exposes helpers for opening apps, reading screen content, tapping, scrolling, typing, and verifying actions. On iPhone, it uses the macOS iPhone Mirroring window as the transport: screenshots are captured from the window, Apple's Vision framework performs OCR and returns tap-ready coordinates, and HID-level CGEvents provide taps, long presses, drags, flicks, scrolling, Unicode typing, and shortcuts. On Android, it uses ADB over USB or Wi-Fi, combining screenshots with the phone's accessibility tree for text and element bounding boxes. Actions can be verified by capturing the screen again, with the screenshot serving as the ground truth rather than relying on a DOM. Each invocation is self-contained rather than relying on a daemon.
Ante is a self-contained terminal coding agent and agent harness developed by Antigma Labs. It is distributed as a single Rust executable with no runtime dependencies and is designed to work with provider APIs, subscriptions, or local GGUF models. Its core embeds Grep and git operations in one process and uses a managed version of llama.cpp for local inference. In offline mode, it runs the coding-agent loop entirely on the user's machine without an API key, account, or internet connection; settings profiles can define the agent and its system prompt. The project also supports multiple providers, multi-agent orchestration, MCP skills, and memory. Ante is in beta preview, with breaking changes and incomplete functionality expected. The repository states that macOS and Linux are supported and recommends WSL for Windows.
An open-source collection of Markdown output styles for Claude Code, Codex, and other coding agents. It changes how an agent communicates rather than how it codes: responses are answer-first, written in plain English, and formatted for skimming. The collection includes Attention-kind, which spaces points apart, uses arrows and bold emphasis, and expands only when useful; Spartan, a terse style with no warmth; and Rundown, a brief-briefing style. Each style is a single Markdown file that can be added and switched on independently.
OpenMausBot is an open-source, local-first chat application for managing a team of AI bots as separate contacts. Each bot can have its own personality, model, conversation thread, computer, and connected applications, using agents launched through locally installed Claude, Codex, or Grok command-line tools and existing user logins. A local harness server on 127.0.0.1 manages agent processes, transcripts, keys, and events in the user's local OpenMausBot data directory. Bots can work through a cloud Linux desktop, an isolated local virtual machine, or—where supported—the host computer. Shell commands, file edits, and questions are routed through a permission broker and shown as approval or response cards. The application includes model selection, bot and conversation management, browser-accessible desktop takeover, and connected applications through Composio, including services such as Gmail, Slack, GitHub, Notion, and Linear. The repository provides desktop distributions for macOS, Windows, and Ubuntu, with Ubuntu Wayland host control disabled according to the README while a stated issue is resolved.
Rakazo is an open-source platform for running persistent AI teammates. Each bot has conversations, memory, routines, and history, and can access a browser, terminal, files, and a graphical desktop. Users can access bots through the web app, Electron desktop app, or Expo mobile app, and can take control of the graphical desktop when needed. The platform supports shared team computers and isolated private computers, bot delegation to peer bots or short-lived subagents, voice interaction, and user-provided model credentials through Pi. It can use Docker, E2B, Daytona, Box, or trusted local computers as computer providers, and supports integrations through Composio, Pipedream Connect, MCP, OpenAPI, and Treg sources. Rakazo can be self-hosted with Docker and is also available as a managed application. The repository describes it as being in beta and identifies a TypeScript stack using React, Vite, Tailwind CSS, Electron, Expo, Hono, oRPC, PostgreSQL, Prisma, Better Auth, and Graphile Worker.
pgbot is a read-only PostgreSQL observability and health-diagnosis tool for AI agents, applications, and operators. A static binary connects to PostgreSQL, reads the database's own statistics views, and produces deterministic, findings-first health reports, including a health score, critical/warning/note findings, verified healthy subsystems, and change information from local baselines. It provides focused commands for indexes, queries, tables, and vacuum, along with versioned JSON output for agents and scripts and an MCP mode. Its optional ask and explain commands add an AI interpretation of the same findings; inspection and database queries otherwise require no model key or external service. The project is in beta and uses a read-only pg_monitor role with session-level read-only, statement, and lock timeouts as additional safeguards.
img2threejs is an agent skill that reconstructs an object or character from a reference image as a code-only, procedural Three.js model. It generates a TypeScript THREE.Group factory using primitives, procedural shaders, and generated geometry rather than photogrammetry, mesh extraction, or downloaded art assets. The generated scene includes runtime structures such as pivots, sockets, and colliders for animation, and the project documents separate hard-surface and anatomy-aware reconstruction paths. It runs under Claude Code, Codex, or OpenCode and provides live browser demos whose models can be inspected as generated source.
Personal Model is an open-source, local-first AI memory runtime from Intuition Lab for giving coding agents evidence-linked context about a user. After macOS permissions are granted, it captures focused activity from applications on the user's Mac and builds a portable HUMAN.md-style personal context model, storing the data locally and allowing it to be inspected, corrected, exported, or deleted. The runtime progressively organizes sourced observations and events into relationships and changes, supported patterns, higher-order structures, and an integrated current model. It retains source receipts for important claims so later evidence can strengthen, revise, or overturn inferences, then exposes this context through MCP to trusted clients including Claude Code, Codex, Cursor Agent, Claude Desktop, and other compatible tools.
AGENTS.md is an open format for guiding AI coding agents through project-specific context and instructions. It provides a dedicated, predictable file—similar to a README for agents—where projects can document development-environment commands, testing and linting procedures, package or project conventions, and pull-request requirements. The format is documented by the agentsmd project, which also maintains a basic Next.js website with examples.
An Apache-2.0-licensed open-source Go SDK from Grafana for building AI-powered backends and agents. It provides GenerateText and StreamText APIs for calling language models, returning complete or streamed responses, executing Go functions as tools, generating schema-validated structured output, and running multi-step tool workflows, with approval for consequential tool actions. The SDK supports Anthropic, Amazon Bedrock, OpenAI, OpenAI-compatible APIs, and Grafana's hosted endpoint, along with retries, configurable timeouts, fallbacks, logging, Prometheus metrics, and Agent Observability. It follows the design of Vercel's AI SDK and is wire-compatible with its TypeScript React frontend hooks, including useChat, useCompletion, and useObject, allowing Go backends to stream Server-Sent Events directly to an existing React frontend without a protocol adapter.
Zeron is a local control layer for coding agents, including Claude Code, Codex, Cursor, Grok, Hermes, and Pi. Each device runs a small engine that stores agent sessions locally by default, without requiring an account or network connection. Optional synchronization lets users start an agent on one device and follow or control it from another; an always-on machine such as a VPS can keep agents running after a laptop is closed. The Linux installer starts a daemon that persists across reboots, while macOS users can install the desktop release or build from source. Zeron is licensed under the MIT License. The videos refer to the project as Comet.
icm-architect is a Claude skill that designs processes, ideas, and problems as ICM (Interpretable Context Methodology) workspaces, using folder structure as agent architecture, or restructures an existing folder, repository, or vault. Numbered folders encode sequencing, hierarchy scopes context, and plain Markdown files store state, allowing an agent to orient and act by reading the relevant files. In build mode, it extracts stages, human approval points, and stable versus per-run elements, then scaffolds a workspace using one of six forms: Pipeline, Umbrella, Record library, Knowledge bundle, Context map, or System map. In restructure mode, it audits files as catalog, contract, factory, product, or dead, proposes a migration map for approval, then migrates and validates the result. The walk test checks whether an agent with no prior memory can orient, act, and report status from the workspace alone. It can be installed as a Claude Code skill or uploaded to Claude applications, and is MIT licensed.
unlazy is an agent skill for enforcing completion discipline in substantial AI-agent tasks. It requires an acceptance ledger to be written first, with runnable CHECK commands and EXPECT conditions; its gate checker reviews commands, executes approved gates, records evidence, and can reverify completed work. The skill also supports a Depth Tree method that splits tasks into fresh-context subtasks with integration checks, giving each leaf the full task time budget. It can be installed for supported agents with the skills CLI or manually for Claude Code and Codex CLI; its checker and optional hook require Node.js 16 or newer and no third-party runtime packages.
Endoplexity is a Chrome MV3 side panel and local bridge for agentic control of the browser a person is already using. It lets Claude or Cursor agent CLIs operate existing tabs and logged-in sessions by clicking, typing, filling forms, navigating, switching tabs, uploading files, and reading pages, without sending requests directly to a model or requiring a separate metered API key. The side panel owns the Chrome DevTools Protocol connection and communicates over an origin-pinned WebSocket with a bridge on localhost; the bridge exposes browser tools over token-gated MCP/HTTP and enforces the safety policy, including approval gates and autonomy modes. Pages are provided to the agent as accessibility-tree snapshots rather than raw HTML, and actions return the resulting page state so subsequent turns can resend only changed lines. Its file-reading tool extracts text from PDFs, DOCX, XLSX, PPTX, CSV, JSON, Markdown, and other text files.
NorthCinder is an open-source, local-first MCP server for AI shopping agents. It compares products from user-selected sources against a buyer's criteria, explains rankings and exclusions, shows source facts and unverified details, and normally returns up to three useful options rather than claiming one universal best product. Its research workflow provides separate product and seller guides, creates a research plan, and uses controlled research tools; results remain provisional when sources conflict or do not identify the exact item or seller. Purchasing is a separate human-in-the-loop decision: each checkout requires fresh approval for one exact offer and unit, with the merchant, variant, price, known total, and spending cap signed into a single-use approval. It rejects raw card details, using an opaque payment token for supported automated checkout or handing the buyer a cart link. NorthCinder runs alongside an MCP-capable AI application. Its local setup requires Node.js 20 or later; the init command stores configuration locally and starts the MCP server and search engine in one process. The repository states that there is no hosted NorthCinder account or cloud service, and that order outcomes remain local.
TrueForge is an open-source, vendor-neutral agent harness developed by TrueFoundry. It runs the agent execution loop, including model calls, MCP tool use, skills, sandboxed code and file execution, approvals, context management, and session state. Agents can use configured model providers, remote MCP servers, git-backed SKILL.md instruction packs, and on-demand sandboxes; context features include subagents, deferred tool loading, Code Mode, large-result offloading, and compaction. TrueForge exposes agents through a bundled chat UI, an HTTP API with a TypeScript SDK, and an embeddable UI SDK. It supports local mode with SQLite and hosted deployments using Postgres and Redis through Docker Compose or Helm; the repository warns that local mode is intended for personal use on localhost rather than production or internet-facing deployment.
sloptrim is a local prose linter and coding-agent plugin that detects patterns associated with AI-generated writing when an agent saves a document. It extracts prose from supported text and office formats, scores it on a 0–100 scale, and reports suspicious spans for revision; it analyzes writing patterns rather than determining authorship and does not process code. The command-line tool uses Python's standard library, requires no model or network connection, and keeps text on the local machine. It integrates with Claude Code and can be initialized for other agents through an agent contract and editor-rule files.
J-Space Cognition Suite is a model-agnostic, inference-time control system packaged as a cross-platform AI-agent Skill for deep reasoning, long-horizon work, tool use, verification, and recovery. It leaves model weights and training unchanged, organizing an agent's working representations through one entry point and nine selectively loaded modules supported by four references. Its fast, full, and loop operating modes use selective workspace loading, a shared broadcast hub for constraints and values, dense internal reasoning traces, explicit intermediate steps before conclusions, metacognitive routing of confidence and failure signals, and bounded empirical verification. An optional standard-library controller records durable task state, including goals, next actions, checkpoints, open questions, seams, and recovery state. The suite is intended for low-friction integration with AI hosts that support Skills or equivalent system/developer-instruction mechanisms.
Docker Sandboxes is a Docker security feature for running AI coding agents and tools inside isolated micro virtual machines. Each sandbox has its own kernel, filesystem, and network, allowing agents such as Claude Code to run with reduced access to the host machine.
Iris is a Rust command-line tool and local stdio MCP server for capturing screenshots of live websites with an installed Chrome-family browser such as Chrome, Chromium, Edge, or Brave. It can capture viewport or full-page images, emulate mobile sizes and user agents, apply dark color schemes, frame the first matching element with optional padding, wait for selectors or page content, and process URL batches concurrently or from standard input. The same binary exposes an MCP `capture` tool that returns an inline image with structured metadata and can optionally write an output file. It is distributed as the `iris-screenshot` crates.io package or through an install script; building from source requires Rust 1.88 or newer.
Wake is a native desktop application that gathers coding-agent sessions from local data directories into a single searchable library. Built with Rust and GPUI, it reads supported agent histories read-only, groups them by agent and project, watches files for incremental updates, and indexes transcripts with SQLite FTS5 trigram search, including code substrings and CJK text. Its transcript view renders messages, collapsible tool-call clusters, thinking summaries, and syntax-highlighted code. Wake can resume supported conversations in a terminal at the original project directory, and also provides session management, Markdown export, deletion with tombstones, and library statistics. Data remains local; the application does not make background network requests and only contacts GitHub when an update is explicitly checked. It is macOS-first, with experimental Linux support and experimental Windows support.
Amagine3D is an open-source 3D capability layer for hardware creation, developed by Amagine. Its parametric CAD workflow turns natural-language hardware requirements, reference images, and key dimensions into editable enclosures and assembly structures around internal components, producing Python and build123d source code alongside STEP, STL, or color-aware 3MF exports. A 3D-native agent first organizes the requirements into a design brief, then runs the generated source in a browser geometry runtime. It uses the resulting model state and check results for dimensions, part connectivity, interference, and motion clearance to revise or accept the design. The workflow supports multipart structures such as covers, hinges, and latches, including assembly clearances and printing tolerances. Generated parameters can be adjusted in the workbench and written back to the source without regenerating the model. The system can preview, measure, modify, and save complete designs and their check reports.
macOS Harness is an experimental, MIT-licensed, macOS-only Python harness from browser-use that gives an LLM or coding agent raw primitives for controlling a Mac in one persistent Python process, without app-specific tools, recipes, or framework rails. Its six core primitives—`see`, `key`, `type`, `click`, `ax`, and `script`—capture native and Electron app windows, send keyboard and coordinate input directly to an application process, expose Apple Accessibility and Apple Events, execute AppleScript, and draw a click-through pointer without moving the physical cursor. The agent can write missing task logic in ordinary Python during execution. The same process provides access to a real, logged-in Chrome browser through Browser Harness, as well as the local filesystem and shell commands through Python, `Path`, and `subprocess`. It can capture background application windows without bringing them to the foreground and does not activate or raise the target app. The project includes installation and skill-registration workflows, a `doctor` command for checking required macOS permissions, and verification instructions. Anonymous telemetry is enabled by default and records the CLI command category, success, duration, package version, operating system and architecture, and detected agent client; the project states that it does not record prompts, app names, screenshots, UI text, scripts, paths, or window titles, and provides `macos-harness telemetry disable` to turn telemetry off.
OpenSpec is an open-source, tool-agnostic spec-driven development framework from Fission AI for AI coding assistants. It stores requirements and development artifacts as plain Markdown files in a repository, using an `openspec/` structure containing specifications and proposed changes. Its workflow supports exploratory discussions, `/opsx:propose` for generating a proposal, requirements and scenarios, a technical design, and implementation tasks, followed by `/opsx:apply` to implement the tasks and `/opsx:archive` to update the specifications. Coding agents can interact with it through slash commands or an MCP server. The project is designed for iterative, brownfield development and supports shared or cross-repository requirements through beta Stores. The CLI requires Node.js 20.19.0 or higher and is installed with npm.
CarWatch is an open-source, offline in-car AI agent from ThinkOffApp that runs on a Raspberry Pi 5 with a locally hosted language model. It joins chat rooms as a vehicle agent, answers questions from the car's owner's manual using lexical retrieval-augmented generation and page citations, and reads live vehicle and system data while stating when information cannot be sensed. A continuous energy-based voice listener and whisper.cpp provide local speech input without a wake word, with responses played through the car's speakers. The system can monitor OBD and engine data, send departure and arrival messages, trip summaries, and dashcam clips, and expose a phone dashboard for approvals, replies, model selection, and maintenance. The repository describes systemd-managed services for the model server, room agent, voice listener, dashboard, and engine watcher, with Python standard-library code and no cloud subscription required.
Factory is a reference software factory for Claude Code and Codex that installs a repeatable, version-controlled software-delivery workflow into an existing GitHub project. GitHub Issues serve as the work queue, while committed policies, skills, labels, handoff comments, pull requests, and run records preserve state between fresh agent sessions. Scheduled agents triage issues, route them to implementation, specification, questions, or blockers, claim bounded work, implement it on a branch, run configured type, lint, test, build, audit, and architecture checks, obtain independent verification, and open draft pull requests. An independent verifier reads the diff and checks that the new test fails without the implementation. Humans retain responsibility for ambiguous requirements, system design, significant changes, and merging pull requests. The repository has no custom orchestrator or queue service. Claude Code routines provide the default scheduling and compute, with a thin Codex adapter using the same policies, gates, and evidence files; GitHub events or an optional API-triggered Action can also start runs. It is configured through files such as a human-owned charter and gates script, and includes a /factory control room backed by live issues, pull requests, and run records.