Find AI tools by the job you need done.

Generates real-world locations inside Minecraft with a surprisingly high level of detail.

A PrismML family of low-bit multimodal models derived from Qwen3.6-27B, with 1-bit and ternary weights, local inference paths, and a runnable demo repository.

A Cohere Labs 30B-total, 3B-active mixture-of-experts coding model for code generation, agentic software engineering, and terminal tasks, with public BF16 and FP8 Hugging Face weights, Apache 2.0 licensing, and OpenCode or Cohere API try paths listed by official materials.

A Cohere Labs Command A+ model variant with W4A4 quantization, positioned around agentic tool use, multimodal inputs, multilingual work, long context, and Cohere-reported lower hardware requirements.

A newer DeepSeek OCR model release for image/PDF OCR, document-to-Markdown workflows, dynamic resolution, vLLM/Transformers inference, and visual causal flow research.

A DeepSeek model family release positioned around long-context intelligence, reasoning modes, coding benchmarks, and agentic task evaluation.

A Google DeepMind Gemma 4 model family collection with public checkpoints including Gemma 4 12B, a dense multimodal model Google describes around local agentic workflows, native audio input, and encoder-free vision/audio handling.

A Z.ai flagship text-generation model positioned around 1M-token context, long-horizon coding, agentic engineering, public model weights, API access, and local serving paths.

Z.ai's 753B text-generation model for complex coding and long-horizon agent work, with public weights, an official 1M-token evaluation path, adjustable reasoning effort, and several technical serving options.

A Z.ai 320B-total, 18B-active multimodal mixture-of-experts model for coding, agent workflows, visual input, and long-context work, with a 1M-token context window, public FP8 and BF16 weights, API access, and several technical serving paths.

A 0.9B multimodal OCR model for complex document parsing with several self-hosted or API deployment paths.

A low-bit on-device translation model from AngelSlim, positioned around 33-language offline translation, GGUF access, Android demo use, and 1.25-bit compression.

A Tencent-Hunyuan multilingual translation model family with 1.8B, 7B, and 30B-A3B variants, 33-language support, an AngelSlim 1.25-bit on-device option, IFMTBench, training notes, and several deployment paths.

A Tencent Hy Team 295B-parameter MoE language model for long-context reasoning, coding, tool use, and agent-style workflows, with public Hy3 and Hy3-FP8 weights, Apache-2.0 licensing, and vLLM or SGLang serving notes.

Tencent Hy Team's preview-stage 770B-total, 49B-active Mixture-of-Experts language model for coding, document and analysis work, game development, research, tool use, and long-context tasks, with a 1M-token context window, public BF16 and FP8 weights, and dedicated vLLM or SGLang deployment paths.

A Thinking Machines Lab open-weights multimodal model with text, image, and audio input, adjustable reasoning effort, a 1M-token maximum context window, public BF16 and NVFP4 weights, Tinker fine-tuning access, and deployment recipes for major inference frameworks.

An InternLM model series built to reason across scientific paper pages, molecular and material structures, protein sequences, and physical time-series signals, with current Intern-S2 previews, earlier S1 checkpoints, public weights, and deployment guides.

An NVIDIA Isaac GR00T N1.7 vision-language-action model family for humanoid and generalist robot skills, with a 3B model, post-trained variants, GitHub code, inference and fine-tuning notes, LeRobot-format workflow support, and official robotics developer materials.

A publicly available 8B vision-language interaction model and deployable system that watches a video stream, decides when to speak or stay quiet, and can delegate harder tasks while keeping the stream in view, with time-aligned data, training materials, and vLLM-based setup paths.

Moonshot AI's open-weight native multimodal agentic model with a 2.8T-parameter MoE architecture, 104B activated parameters, a 1M-token context window, public weights, API access, and deployment guidance for long-horizon coding, knowledge work, reasoning, and visual tasks.

A multimodal agentic model positioned around long-horizon coding, tool use, autonomous execution, and broader software workflows.

A Moonshot AI coding-focused agentic model built on Kimi-K2.6, with a 256K context length, image and video input notes, preserve-thinking behavior, multi-step tool-call materials, native INT4 quantization, and deployment paths through vLLM, SGLang, KTransformers, and Moonshot API access.

An NVIDIA kinematic motion diffusion model for generating human and humanoid-robot motion from text plus pose, joint, waypoint, and path constraints, with local inference, a timeline demo, motion exports, official docs, and benchmark materials.

A Krea AI open-weight text-to-image model family with an undistilled Raw checkpoint for fine-tuning and LoRA training, an eight-step Turbo checkpoint for inference, official local code, Diffusers, SGLang, ComfyUI, hosted routes, and the Krea 2 Community License.

A community-made distillation LoRA that runs Krea 2 Turbo in four generation steps, with Diffusers weights, a stock ComfyUI workflow, rolling numbered checkpoints, and an independent Hugging Face demo.

Compare hosted testing with a 75.2 GB Q4 local route, then inspect Poolside’s published trajectories and documented tool-call limitations before deciding whether this long-context coding model fits.

A ByteDance Research unified multimodal model for image and video understanding, generation, and editing, with model files, demos, inference scripts, Gradio setup, benchmark scripts, and a stated 40GB VRAM inference requirement.

Liquid AI's two-size family of 230M and 350M bidirectional masked-language encoders for fine-tuning classification, token-level tasks, retrieval, reranking, and semantic similarity, with 8,192-token context, downloadable weights, official demos, and reproducible evaluation materials.

Liquid AI's 2.69B-parameter text model for local tool use, multi-step agent workflows, extraction, RAG, and long-context tasks, with a 131,072-token context window plus native, GGUF, ONNX, and MLX formats.

Liquid AI's 230M-parameter LFM2.5 text model for lightweight on-device agentic pipelines, data extraction, and edge inference, with Hugging Face weights, GGUF, ONNX, and MLX variants, 32K context notes, tool-use guidance, and official docs/blog materials.

A compact 350M-parameter model for on-device deployment, with 32K context and export paths for several local runtimes; Liquid AI recommends it for extraction, structured output, and tool use rather than knowledge-heavy or programming tasks.

A Liquid AI hybrid model with 8.3B total parameters, 1.5B active parameters, long-context support, tool-use notes, local formats, and deployment paths for edge and agentic workflows.

Liquid AI's 3.1B vision-language model for on-device image understanding, grounding, object detection, OCR with layout annotations, and tool use, with native, GGUF, ONNX, and MLX model paths plus a browser demo.

An inclusionAI sparse language-model collection led by Ling-3.0-flash, with standard and FP8 checkpoints for coding, tool use, long-context work, and efficiency-focused agent serving.

An inclusionAI trillion-parameter model for demanding reasoning, coding, tool use, and multi-step agent work, with public weights, publisher-reported evaluations, multi-GPU serving notes, and hosted access paths listed at review time.

An inclusionAI instruct model positioned around faster responses, token efficiency, tool use, multi-step planning, and agent-oriented workloads.

A feed-forward 3D foundation model for streaming scene reconstruction, positioned around geometric consistency, long sequences, and efficient real-time inference.

A Meituan LongCat open-weights MoE language model with 1.6T total parameters, about 48B active per token, native 1M-token context, coding and agentic-workflow framing, and base, FP8, and INT8 model pages.

A Lightricks audio-video model family with gated component weights, synchronized sound, text-to-video, image-to-video, multishot generation, local Python and ComfyUI paths, fine-tuning tools, and a separate hosted API.

A series of generative 3D world models from NVIDIA, positioned around explorable scenes, 3D consistency, and world-scale generation workflows.

A JetBrains 12B MoE model family for software-engineering AI workflows, with 2.5B active parameters per token, multiple public checkpoints, 131,072-token context notes, tool-use and agent-workflow framing, deployment examples, and a technical report.

A Xiaomi MiMo model family positioned around multimodal understanding, agentic workflows, long-context use, and Pro variants for harder software and tool-heavy tasks.

An OpenBMB 1B-class language model for local assistants, coding agents, tool-use, reasoning, and long-context workflows, with 131K context, Think / No Think modes, standard LlamaForCausalLM architecture, and deployment paths across Transformers, vLLM, SGLang, Docker, GGUF, Ollama, LM Studio, and MLX.

A MiniMax audio-video generation system with public H3-Base weights for text, image, video, and audio reference workflows, native stereo output, 4-to-15-second clips, local 768p generation, a hybrid 2K path, and a direct hosted API.

A LightX2V community LoRA project that distills MiniMax H3 into four- and eight-step video-with-audio workflows, with Diffusers and ComfyUI checkpoints, single- and multi-GPU inference code, and a 768p four-step option.

A large MiniMax model focused on agentic work, software engineering, tool use, and complex productivity workflows.

A MiniMax native multimodal model with public ModelScope and Hugging Face pages, 1M context, about 428B total parameters and 23B activated parameters, MiniMax Sparse Attention materials, thinking and non-thinking modes, and deployment paths for Transformers, vLLM, and SGLang.

An OpenMOSS 11B vision-language model family with Realtime, Instruct, and Base checkpoints for continuous video streams, offline multimodal work, and further training, plus public inference and fine-tuning paths.

Meta's downloadable 30B dense model for local agent, coding, tool-use, and text-and-image workflows, with a 131K context window, adjustable reasoning effort, and an official 17 GB GGUF model file for 24 GB-class setups.

An NVIDIA 14B text-generation model from the Nemotron-Labs-Diffusion family, focused on switching between autoregressive, diffusion-style parallel decoding, and self-speculation for project-reported decoding efficiency gains.

Cohere Labs' downloadable 2.4B vision-language model for native-resolution documents, charts, OCR, visual grounding, image questions, and task-specific fine-tuning, with multilingual and multi-image input plus Transformers, NVIDIA AutoModel, Axolotl, and community MLX paths.

A NuMind vision-language model for template-guided JSON extraction and document-to-Markdown conversion, with text and image inputs, optional reasoning, multi-page PDF examples, a hosted demo path, full weights, and GGUF variants.

An NVIDIA 4B content-safety model for classifying prompts, optional images, and model responses against standard or custom policies, with a Hugging Face model card, launch post, released dataset, Transformers, vLLM, SGLang, and NVIDIA NIM paths to inspect.

An Ai2 remote-sensing foundation model family for satellite imagery and planetary-scale mapping, with v1.2 Nano, Tiny, Small, and Base models, model weights, training code, and a technical report.

An Ornith AI reasoning-model family for coding and agent workflows, with 9B, 35B-A3B, and 397B checkpoints, quantized serving routes, and a training loop that generates tasks, scaffolds, and solution rollouts.

A Qwen language world model for simulating agentic environments, with Apache-2.0 Hugging Face weights, a GitHub repo, AgentWorldBench data, prompts, evaluation/deployment scripts, and domains including MCP, search, terminal, software engineering, Android, web, and OS tasks.

A sparse open-weight multimodal model with 35B total and 3B active parameters, positioned around agentic coding, tool use, long-context work, and software workflows.

Qwen's open-weight 27B dense multimodal model for coding, professional work, research, image and video understanding, and longer agent tasks, with controllable reasoning and a 262K native context window.

Qwen's experimental open-weight preview of the architecture planned for Qwen4, pairing a 125B multimodal main model with 6B active per token, a roughly 360 GB repository, 262K native context, and day-one serving recipes.

A StepFun multimodal MoE model collection with BF16, FP8, NVFP4, and GGUF variants, 256K context notes, tool-use and agent-workflow framing, and deployment paths across vLLM, SGLang, Transformers, and llama.cpp.

A Google Research time-series forecasting foundation model with a public GitHub repo, TimesFM 3.0 and archived checkpoint paths, a PyPI package, BigQuery ML documentation, Apache-2.0 source and weights through 2.5, and the separately named timesfm-non-commercial-license-v1.0 for the 3.0 pretrained weights.

Google DeepMind vision-language encoders with original TIPS and current TIPSv2 materials, focused on patch-text alignment and evaluated spatial awareness.

A Microsoft 3D generation model for high-fidelity image-to-3D asset creation, using O-Voxel structured latents, PBR materials, inference code, and training tools.

An Arcee AI sparse mixture-of-experts model family presented for multi-turn reasoning and tool use, with long-context handling, quantized variants, and substantial deployment requirements to check in the model card.

A downloadable 3B model built from SmolLM3-3B for formal-logic work, including entailment, semantic parsing, Lean-oriented tasks, procedural reasoning, and rule induction, with merged Transformers weights and five GGUF options for local inference.

A Baidu OCR model and code release for one-shot long-horizon document parsing, with public GitHub, Hugging Face, ModelScope, and arXiv materials, Transformers and SGLang examples, and batch image/PDF inference paths.

A promptable 3D detection system for real-world scenes, positioned around text, point, and box prompts for spatial perception workflows.

A small Zyphra mixture-of-experts reasoning model with public weights, 760M active parameters, 8.4B total parameters, deployment notes, and project-reported math and coding evaluations.

Audio8's CPU-oriented ONNX package for compact multilingual text-to-speech and zero-shot voice cloning, with INT8 generation models, local voice registration, and HTTP and OpenAI-compatible speech endpoints.

A compact seven-language speech-recognition model with a Transformers checkpoint, optional hotword boosting, a self-contained CPU ONNX package, and an iPhone demo and Swift SDK for local transcription.

A 3B English and Chinese text-to-speech model for reference-free voice design, reference-guided voice direction, cloning, vocal events, and streaming, with CUDA-focused inference and the provider-declared BreezeBlue Research and Non-Commercial License.

A 2B parameter automatic speech recognition model for audio-in, text-out transcription across 14 languages.

A text-to-speech model with detailed control over prosody and emotional delivery.

A very small text-to-speech model designed to stay lightweight without feeling toy-like.

A compact 82M-parameter text-to-speech model from hexgrad, with model facts, usage examples, voice materials, samples, a demo Space, and a linked GitHub inference library.

A Liquid AI Hugging Face collection for Japanese-tuned LFMs, grouping LFM2.5-1.2B-JP-202606 and LFM2.5-Audio-1.5B-JP materials for Japanese text, tool use, structured outputs, ASR, TTS, and speech-to-speech workflows.

A robust automatic speech recognition project for messy real-world audio, with code, inference and training paths, Hugging Face weights, a technical report, Voices-in-the-Wild-2M, and project-reported results across difficult acoustic scenarios.

A Xiaomi MiMo speech-recognition model focused on Mandarin, English, Chinese dialects, code-switched speech, noisy audio, songs, and multi-speaker transcription.

An audio-understanding model family for speech, sound, music, captioning, time-aware QA, ASR, and reasoning over real-world audio.

A speech and sound generation model family covering TTS, voice design, spoken dialogue, realtime speech, compact speech generation, and MOSS-SoundEffect-v2.0 text-to-audio materials.

A 0.1B speech generation model covering 20 languages, voice cloning, a repository-recommended ONNX CPU path, browser and CLI use, and released fine-tuning code.

An NVIDIA 600M-parameter multilingual streaming automatic speech recognition model for low-latency voice AI and high-throughput transcription, with NeMo loading and streaming paths, documented language tiers, and performance tables.

An NVIDIA 11B full-duplex conversational speech model with streaming speech understanding and generation, realtime interruption handling, a separate tool-call channel, and official offline and container deployment paths.

A real-time full-duplex speech-to-speech conversational model with persona control through role prompts and voice conditioning.

A Japanese-centric text-to-speech system from SB Intuitions, with Japanese and English generation, style transfer, and zero-shot voice generation support.

An on-device multilingual text-to-speech system built around ONNX Runtime, with local inference, 31-language support, expression tags, a local HTTP server with OpenAI-compatible endpoints, and examples across browser, mobile, desktop, and edge runtimes. The maintainers say the repository will be archived with no further development or official support.

A speech-language model that aligns speech and text into a single synchronized stream.

A Microsoft Research speech-recognition model compressed for offline CPU inference, with two ready-to-use GGUF components, an official C++ runtime, a CPU demo, and documented x86 AVX2 and Arm NEON results.

A multilingual text-to-speech model with voice design, controllable voice cloning, and streaming support.

A locally runnable music model with 2B and XL 4B variants for full-song generation, reference-guided creation, repainting, accompaniment, stem separation, and lightweight style training.

A framework for generating animatable 3D assets from a single image, with mesh, skeleton, and skinning outputs for downstream animation and simulation workflows.

A 10B research model family for text-to-image generation and instruction-based image editing, with Base, Turbo, Edit, and Edit-Turbo checkpoints, bilingual Chinese-English text rendering, local inference code, and public demos.

A framework for co-generating 3D human motion and realistic videos, with a focus on motion-conditioned video generation and training workflows.

The FastVideo realtime video generation and editing platform, with backend and web UI setup, local GPU, B200, Docker, Modal, readiness checks, and mock-backend workflows.

A local image-generation interface built around prompt-focused SDXL workflows, with Windows downloads, Colab access, inpainting, outpainting, image prompts, and presets.

A Meituan LongCat audio-driven avatar video model for single- and multi-person generation, with audio-text-to-video, audio-image-text-to-video, video continuation, model weights, GitHub quickstart, and project-reported evaluation materials.

An NVIDIA Labs infrastructure codebase for long video generation, with LongLive 2.0 NVFP4 and FP8 inference paths, parallel training and inference, multi-shot and image-to-video support, async decoding, LongLive-RAG, model links, docs, and configs.

Mage-Flow pairs text-to-image generation with instruction-based image editing in one Microsoft 4B model family, with Base, RL-aligned, and four-step Turbo checkpoints plus local and hosted demo paths.

A portrait image-animation framework for live-streaming-style video generation research, with offline and online inference, pretrained weights, a Web UI, and acceleration notes.

An NVIDIA Labs codebase for efficient high-resolution image and video generation, with Sana, Sana-1.5, Sana-Sprint, Sana-Video, Sana-WM world-model work, training and inference pipelines, model zoo links, and ComfyUI and diffusers paths.

An agentic video-generation framework for turning ideas, scripts, or longer narratives into planned video workflows, with a project-based web interface, interactive agent loop and terminal UI, storyboards, shot planning, previews, render checkpoints, and configurable model providers.

A music-to-dance video model and framework that uses a reference image, a full music track, and a dance-style prompt, with separate global keyframe planning and local refinement stages for longer outputs.

An agent memory layer that distills agent-run learnings into Markdown skill files, with cloud and self-host paths, Python and TypeScript SDKs, dashboard/API surfaces, sandbox and disk tools, and cross-framework reuse.

A Python framework for tool-using agents and multi-agent networks. AG2 v1 coordinates agents through a hub and typed channels; older AutoGen-derived classes and patterns remain in the separate AG2 Classic package.

A large catalog of specialist agent instruction files, with installers and converters for using selected roles across Claude Code, Codex, Cursor, Gemini CLI, OpenCode, and other coding tools.

A CLI routing layer that helps command-capable agents reach web, social, repository, video, RSS, and search sources through ordered backends. For multi-backend channels, its doctor command reports the active backend, while default setup only checks the machine unless system changes are explicitly authorized.

A draft Agentic Resource Discovery specification for publishing and searching agentic resources across federated registries, with v0.91 ARD entries and ard.json manifests, REST search, trust metadata, a public Apache-2.0 spec repo, and a Hugging Face Discover implementation for Skills, Spaces, and MCP servers.

A Python agent framework with ReAct agents, tools, skills, human steering, memory, planning, multi-agent workflows, MCP connections, observability, and deployment paths.

A self-built VS Code extension and GitHub Copilot app canvas that reads local AI coding-session logs from several harnesses and turns them into dashboards, practice signals, anti-pattern findings, output views, reusable-skill suggestions, and context-health checks.

An installable skill for AI assistants that searches a regularly updated library of 10,000+ community image prompts, returns a small set of matching examples with sample images, and can adapt a chosen template to a specific brief.

A curated library of medical research agent skills designed to support evidence review, protocol design, data analysis, and academic writing workflows.

A local-first AI workspace for chatting with documents, using agents, connecting local or cloud model providers, adding MCP tools, building agent flows, and running as desktop, self-hosted, or hosted software.

A scriptable command-line manager for finding, installing, inspecting, auditing, and organizing reusable skills across Codex, Claude Code, Cursor, and other AI coding-agent environments.

A local-first operator agent runtime for local or configured cloud models, with browser, file, shell, document, memory, task, skill, MCP, HTTP, and Tauri sidecar paths built around a local control loop and on-disk state.

A prompt-as-code library for GPT Image 2 with a categorized case gallery, reusable visual prompt templates, a live browsing site, and an installable agent skill for turning image ideas into structured prompts.

A browser automation framework for AI agents that can navigate websites, click elements, type into pages, use custom tools, and run browser tasks through code or CLI workflows.

An AI-first knowledge base and workspace system with agents, memory, scheduled jobs, and local file-based storage.

An always-on system that records detailed computer activity for vectorless recall, with local storage and a cloud-model privacy tradeoff.

A multi-agent game-development studio system for Claude Code, organized around specialized agents, workflow skills, hooks, rules, and templates.

A third-party Claude Code plugin with focused SEO skills, specialist agents, site and page audits, schema and AI-search checks, local reports, and optional integrations for live search, performance, analytics, and backlink data.

A self-contained agent skill that combines video captions or a Whisper transcript with timestamped frames so Claude, Codex, and other coding-agent hosts documented by the project can answer questions about video URLs or local files.

An economic benchmark and nanobot integration that gives AI agents professional tasks, tracks model and search costs, evaluates submitted artifacts, and shows quality, income, and balance changes in a dashboard.

A local code-intelligence MCP server that turns repository structure into a persistent knowledge graph for symbol search, call tracing, dependency questions, impact analysis, and coding-agent context.

A local codebase knowledge graph for coding agents, with a Rust parsing engine, MCP tools, symbol relationships, call graphs, framework-aware routes, auto-sync, multi-agent setup paths, and project-reported benchmark results.

Turns repositories into persistent code maps that developers and MCP-connected assistants can query to trace calls, imports, dependencies, and other relationships across a codebase.

An agent tool-integration layer with Python and TypeScript SDKs, toolkits, authentication, sessions, triggers, tool search, and workbench features for connecting agents to external services.

A frontend stack for building agent-native applications with chat UI, generative UI, shared state, backend tool rendering, human-in-the-loop workflows, and React or Angular app paths.

A TypeScript SDK for bringing AG-UI-compatible agents into Slack, Microsoft Teams, Discord, Telegram, and WhatsApp, with streaming replies, native interactive components, files, tools, and approval steps inside channel conversations.

A Python multi-agent automation framework that combines role-based Crews with event-driven Flows for state, routing, persistence, human feedback, tools, memory, and model-provider integrations.

A computer-use agent stack with Cua Driver for background desktop control, agent-ready sandboxes, CuaBot, Cua-Bench, Lume, SDKs, MCP support, and model integrations.

An Agno public data-agent template for asking questions over company data, with read-only SQL analysis, agent-created views in a separate schema, six context layers, a learning loop, AgentOS, Slack, Docker, Railway, and eval paths.

An agent-native personalized tutoring system with tutoring workflows, persistent memory, a web app, CLI access, and a broader learning-support architecture.

A ByteDance long-horizon agent harness for deep research, coding, file work, report generation, skills, sub-agents, memory, sandboxed execution, and message gateways.

A visual platform for building agentic workflows and AI applications with workflow and chatflow builders, model-provider connections, RAG pipelines, tools, APIs, logs, and cloud or self-hosted paths.

A small skills repository for design engineers, with agent guidance around UI polish, animation decisions, strict motion review, and animation vocabulary for prompting designers or AI coding agents.

A Sentient AGI toolkit for benchmark-driven coding-agent skill discovery and improvement, with support for Claude Code, Codex CLI, OpenCode, OpenHands, Goose, Harbor, local/Docker/remote runs, logs, diffs, and reusable evolved skill folders.

A Microsoft Research 27B multimodal computer-use model for browser tasks that works from screenshots, emits coordinate-grounded actions, and ships with public weights, a Fara harness, and a recommended sandboxed MagenticLite path.

An Apache-2.0 terminal agent, reusable runtime, and evaluation suite with stateful ReAct and coordinated Agent Team modes, task-scoped files, approvals, traces, Docker paths, and model-endpoint choices.

An independent Chrome extension experiment for running an on-device browser agent with Transformers.js, WebGPU, Gemma 4, page RAG, tab tools, and semantic history search.

A Git-native agent framework whose identity, rules, memory, tools, and skills live in version-controlled repository files.

A Google Colab command-line interface for connecting local terminal and agent workflows to remote Colab runtimes, with CPU/GPU/TPU provisioning, local script and notebook execution, artifact and log retrieval, REPL or console access, and Linux/macOS-only support at launch.

A public Agent Skills repository for Google products and technologies, including Google Cloud, with installable skills for Gemini API in Agent Platform, cloud basics, onboarding, authentication, observability, and well-architected guidance.

An open-source local AI agent with desktop, CLI, and API access, repeatable Recipes, delegated subagents, model choice, MCP extensions, usage details, and session export.

A local context graph for coding agents, with deterministic repository maps, symbol and call queries, freshness checks, MCP tools, agent wiring, and optional model-written summaries.

A local-first project knowledge graph for code, documentation, schemas, configuration, and optional media, with extracted-versus-inferred edges, query tools, reusable outputs, and coding-assistant skill paths.

A GreenSock skills repository that helps coding agents write GSAP animation code across core APIs, timelines, ScrollTrigger, plugins, frontend frameworks, and performance-sensitive UI work.

A Laude Institute agent microharness whose Bash-based runtime keeps one agent thinking between messages, records its trajectory in inspectable files, and connects the same thought stream to terminal, web, Slack, or Telegram.

A local-first context compression layer for AI agents and LLM apps, with a Python library and CLI, TypeScript SDK, proxy mode, coding-agent wrappers, MCP tools, cross-agent memory, reversible cached originals, and project-reported benchmarks.

A Hugging Face Space for reading Claude Code session JSONL traces, reconstructing sessions in plain English, surfacing production/config/secret-related activity, showing tool and token usage, and answering trace questions with turn references.

A Nous Research agent runtime with CLI and TUI use, persistent memory, reusable skills, scheduled automations, messaging gateways, subagents, tool configuration, provider switching, and multiple terminal backends.

An agent memory system designed to help agents learn over time rather than only recall conversation history.

A local-first desktop workspace where a person and coding agents can share projects, memory, files, skills, tools, apps, and more than 100 documented integrations, with built-in model access or bring-your-own-key options. Selected models and integrations may still connect to outside services.

An H Company computer-use model family for web, desktop, and mobile automation, with 0.8B, 4B, 9B, and 35B-A3B sizes plus FP8, NVFP4, and Q4 GGUF checkpoint paths for local or edge-oriented deployment.

Hugging Face describes hf as the command-line entrypoint for working with the Hub, with agent-mode output, predictable command help, skills support, and workflows for Hub tasks such as search, metadata, downloads, uploads, repos, jobs, collections, and inference.

A Hugging Face GitHub-native AI code reviewer for pull requests, with repository-owned review rules, GitHub Action, GitHub App, and staged web app modes, human editing before publication, and OpenAI-compatible model-provider options.

A Python diagnostic for running fixed behavioral and governance inspections against language models and AI agents, with provider adapters, repeatable suites, cross-provider judging, manifests, scorecards, and CLI, CI, plugin, or agent-skill paths.

A framework for building and deploying agents across creation, research, documents, reusable skills, app integrations, and multi-step work.

A JetBrains Kotlin and Java framework for building AI agents with tools, graph workflows, memory, RAG, MCP, A2A, Agent Client Protocol, tracing, Spring Boot, Ktor, and multiple LLM providers.

A local context layer for data agents that connects SQL warehouse context, semantic definitions, wiki knowledge, CLI search, and MCP tools so agents can reuse reviewable data context.

A cross-client agent skill for 30-day topic briefs across community, market, code, video, social, web, and optional local-file sources, with several install paths, source diagnostics, source-attribution rules, and a Python 3.12+ runtime.

A personal AI harness layer that adds persistent context, memory, skills, structured work, and a local dashboard around a coding assistant, with setup paths for Claude Code, Codex, Cursor, Cline, Gemini CLI, macOS, Linux, and Windows.

A realtime framework for voice, video, and physical AI agents, with Python and Node.js paths, LiveKit room participants, WebRTC clients, telephony support, tools, testing, and deployment options.

A cross-platform desktop app for turning documents into an LLM-maintained wiki, with source traceability, graph and hybrid search, local API and MCP access, and a companion agent skill.

A TypeScript framework for building AI agents and applications with model routing, workflows, human-in-the-loop steps, memory, tools, MCP servers, evals, and observability.

An open-source knowledge-base agent platform for building RAG-backed Q&A assistants and agent workflows, with document upload and web-source collection, vector/full-text/hybrid retrieval, model-provider connections, MCP/tool use, web embedding, Docker/offline deployment paths, and GPL-3.0 licensing.

A memory layer for AI agents and assistants, with library, self-hosted, platform, SDK, CLI, cookbook, evaluation, and integration paths for persistent context.

A Rust-based memory layer for AI agents that keeps documents, embeddings, search indexes, metadata, and recovery state in one portable .mv2 file, with CLI, Python, Node.js, and framework integration paths.

A curated library of portable agent skills for designers and builders using Codex, Claude, Cursor, Aura Build, Lovable, and similar AI coding agents, with workflows for design prompts, landing pages, screenshots, WebGL, animation, frontend systems, and reusable skill folders.

A Cosmic Stack personal AI agent runtime with permission modes, local structured memory, editable personality files, token budgets, provider choices, skills, scheduled work, background service operation, and terminal, web, or messaging channels.

A proxy-based adaptation framework for personal agents that can turn live conversations into reusable skills, keep cross-session memory, and optionally run cloud-backed LoRA training during inactive windows.

A Microsoft framework for building AI agents and multi-agent workflows in Python and .NET, with a separate public-preview Go SDK plus graph workflows, middleware, context providers, observability, and provider choices.

A Microsoft toolkit for adding policy enforcement, identity, sandboxing, audit records, reliability tooling, and the Agent Control Specification runtime layer around AI agents, with Python, TypeScript, .NET, Rust, and Go surfaces.

A Microsoft Responsible AI evaluation harness for AI agents and LLM apps that turns natural-language requirements into generated test scenarios, runs them against models or traced agents, and writes local artifacts for review.

A beta development skills library for AI coding agents, with structured guidance across frontend, fullstack, mobile, shader, document, and media work.

A multimodal web agent from Ai2 that can navigate browser tasks from natural-language instructions.

A task collaboration platform for human and AI-agent teams, with shared issues, comments, agent assignments, local coding-tool runtimes, scheduled work, a CLI, desktop clients, and a self-hosted server path.

An agent and product integration platform for auth, OAuth, API proxying, TypeScript functions, MCP tool calling, observability, and external API access.