Provides a workspace-first, Kanban-backed multi-agent coordination platform that routes goals through specialist lanes (Backlog→Todo→Dev→Review→Done), enforces evidence-based review gates and traces, and runs on both web and desktop runtimes.
Provides reusable “skill” instruction bundles that teach AI coding tools how to author, query, and operate Microsoft Fabric workloads via REST APIs, T-SQL, KQL and notebooks. Includes Copilot CLI/Claude/Cursor integrations, workload-focused bundles, and optional MCP configurations for live data access.
Provides named agents, reusable skills, and MCP data connectors for common financial‑services workflows (investment banking, equity research, private equity, wealth). Available as Claude Cowork plugins or deployable Claude Managed Agents templates—designed as enterprise-ready templates, not turnkey investment advice.
Provides an MCP server and agent skills so AI agents can run keyword research, inspect SERPs, compare domains, and manage backlinks using your DataForSEO data. Self‑hostable TypeScript project with an optional hosted UI (openseo.so) and pay‑as‑you‑go data usage.
Lightweight, Markdown-only skill pack that lets LLM agents autonomously run ML research workflows—literature survey, idea discovery, cross-model review loops, experiment automation and paper writing—designed for Claude Code, Codex CLI, Cursor and local model setups.
Bridges an LLM assistant to your locally running TradingView Desktop via Chrome DevTools Protocol for AI-assisted chart analysis, Pine Script development, and UI automation. Key features: Claude Code MCP integration, a JSON/CLI 'tv' toolset, local-only operation and streamable chart data.
Turns natural-language instructions into runnable trading research: data loaders, strategy generation, backtests, reports, and optional broker connectors. Focuses on a tool-driven agent model (36+ MCP tools, 77 finance skills) and an Alpha Zoo of 452 pre-built alphas for reproducible research and gated agentic trading.
Provides a lightweight Python harness that turns LLMs into working agents with tool-use, skills, persistent memory, permission controls and multi-agent coordination. Ships with a CLI/React TUI, 43+ built-in tools, a plugin/skill system and the ohmo personal-agent for chat gateways. Best for developers prototyping agent workflows and multi-agent experiments.
Turns a repo's code, docs, PDFs, images, and videos into a queryable multimodal knowledge graph for AI coding assistants. Uses deterministic AST extraction for code and LLM-based semantic extraction for other assets, exporting interactive HTML, JSON, and a human-readable audit report.
Stores conversation history verbatim and retrieves it via local semantic search with a structured index (wings/rooms/drawers). Pluggable vector backends and a local-first default mean high recall (benchmarked) without cloud or API keys—useful for agent memory and private RAG.
Generative-AI-enabled timeline video editor for macOS that lets creators generate and edit videos and images directly inside the timeline. Includes a local MCP server for agent integrations (Claude/Codex/Cursor); editor is open-source while generative processing is closed-source and subscription-based; macOS 26 on Apple Silicon only.
Runs goal-driven penetration tests by orchestration of an LLM agent and an MCP toolchain to perform reconnaissance, vulnerability discovery, exploitation, and structured PoC/report generation; supports multiple LLM providers and local MCP integrations; for authorized security testing only.