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.
Provides a single persistent database and open protocol so multiple AI tools share the same memory — built-in vector search, an AI gateway, and capture/skill extensions. Best for teams and power users who want a unified, self-hosted agent memory instead of siloed notes or per-tool caches.
Framework for running agents inside real applications — it exposes shared actions, SQL-backed state, tools, skills, jobs and UI surfaces so agents can act on app state instead of just chatting. Backend-agnostic TypeScript stack with cloneable app templates and visual planning/recap features.
Curated marketplace of Claude Code plugins maintained by Anthropic, separating its own internally built plugins from vetted community submissions. Browse and install directly inside Claude Code via /plugin install {name}@claude-plugins-official.
Hands-on, phase-based curriculum for building end-to-end AI systems from first principles — implement algorithms, run tests, and ship reusable artifacts (prompts, skills, agents, MCP servers) across Python, TypeScript, Rust, and Julia under an MIT license.
A read-only mirror of Anthropic's community plugin marketplace for Claude Cowork and Claude Code, listing vetted third-party plugins in a nightly-synced marketplace.json. Intended for discovering and installing community plugins via the Claude plugin system.
Defines 10 design principles and reference implementations for building agent-native, token-efficient CLIs that reduce token and turn costs for AI agents; includes the TOON output format, benchmarks (browser and GitHub), and an AXI catalog of tools.
Provides a local-first desktop workspace that runs and coordinates AI agents across your files, browser, and third-party tools with a shared, editable memory. Offers built-in models or bring-your-own-keys, one-click OAuth to 100+ integrations, and browser-driven agent automation.
Indexes a repository into a local, queryable index (graph, git, docs, decisions, code health) and exposes task-shaped MCP tools so coding agents and developers get cited answers, symbol-level blast radius, test impact, refactoring plans and dead-code detection; self-hosted (AGPL-3.0) and needs no API key for deterministic analysis.
Manages discovery, quality evaluation, sharing and evidence-driven evolution of skills used by AI agents. Local-first deployment with MCP integration, CLI and Python API, skill lineage and task-based quality summaries for auditable agent workflows.
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.
Curated collection of resources, patterns, and reference implementations for building reliable AI agent harnesses—covering context delivery, tool/MCP design, memory, permissions, observability, verification, and orchestration for production agent engineering.