Forecasts how social scenarios might unfold by running multi-agent simulations: thousands of LLM agents with memory and personalities, seeded from real data, that you steer by injecting variables to 'rehearse the future' in a digital sandbox.
Orchestrates multi-model LLM agents and developer workflows as an OpenCode plugin — runs background specialists, LSP/AST-aware refactors, hash-anchored edits, and built-in MCPs. Designed for agent-driven code automation and multi-model orchestration.
Embeds Claude Code into Obsidian so a Claude-based agent can read, edit, search, and run bash inside your vault. Features include inline edits with diff previews, image analysis, slash-commands, skills/plugins, MCP integrations, and plan-mode.
Normalizes wearable data — heart rate, sleep, activity, steps — from Garmin, Whoop, Apple Health and more behind one self-hosted API, so you write one integration instead of one per provider. Natural-language AI health automations are planned.
On-device search engine for notes, transcripts, and code that blends BM25 full-text, vector semantic search, and a local LLM re-rank — all running offline via node-llama-cpp and SQLite. Ships an MCP server so AI agents can query your knowledge base.
Cross-platform GTD task manager for desktop, mobile, and web that covers the full Capture→Clarify→Organize→Reflect→Engage workflow with a local-first data model and flexible sync backends. Optional BYOK AI copilot and automation (CLI, REST API, MCP) help clarify and break down tasks.
Coordinates about a dozen role-based AI agents — analyst, architect, developer, QA, scrum master — through a CLI, taking a feature from PRD and architecture docs into an automated dev cycle. Runs inside Claude Code, Cursor, Codex, or Gemini.
Provides a CLI-first framework to orchestrate autonomous AI agents and development workflows. Includes role-based agents, the ADE execution pipeline, IDE hooks and an NPX installer for quick setup—best for teams automating planning→development→QA.
Exposes models available in Kiro IDE/CLI (e.g., Claude and other provider models) as local OpenAI- and Anthropic-compatible proxy endpoints so tools and SDKs can use them. Key features: multi-account failover, streaming, tool-calling, VPN/proxy support, and Docker/Python deployments.
Coordinates multiple AI coding agents and persists work state in git-backed hooks; provides convoy-based work tracking, an AI coordinator (Mayor), agent lifecycle/watchdog tooling, and a merge/refinery workflow for reliable multi-agent code work.
Generates summaries from URLs, YouTube videos, podcasts, PDFs, and local audio or video files. Backend-agnostic by design: the same pipeline drives local coding CLIs (Claude, Codex, Gemini) or hosted API providers (OpenAI, Google, xAI).
Runs untrusted AI-agent code, commands, and file operations inside isolated sandboxes that scale from local Docker to Kubernetes. One Sandbox Protocol unifies both runtimes, with gVisor, Kata, and Firecracker isolation and SDKs across five languages.