Lets developers delegate codebase work from terminal, IDE, desktop, web, Slack, or mobile. It reads projects, edits files, runs commands, opens PRs, and asks for permission before changing files or executing commands.
Gives developers direct REST access to Claude models for chat, coding, agents, batch jobs, token counting, and structured outputs. It is best for teams that want Anthropic's newest features without routing through a cloud marketplace.
Runnable starter projects for the Claude API you fork and adapt: a knowledge-base customer support agent, a financial analyst that charts results in chat, plus computer-use, browser-use, and autonomous-coding-agent reference implementations.
Manages provider configs for seven coding CLIs (Claude Code, Codex, Gemini CLI, OpenCode and more) from one desktop app, so switching API endpoints no longer means hand-editing JSON, TOML, or .env files. Adds tray quick-switch and cloud sync.
Provides human preference comparison pairs and red-team conversation transcripts collected by Anthropic for training preference/reward models and studying harmful model behaviors; intended for RLHF and safety research, not for supervised fine-tuning of dialogue agents.
Unifies access to OpenAI, Anthropic, Google and other LLM providers behind one TypeScript API — swap models by changing a string. Adds streaming UI hooks for React, Next.js, Svelte and Vue, plus a tool-calling loop for agentic workflows.
Framework for unit-testing, evaluating and benchmarking LLM systems with ready-made metrics (G‑Eval, hallucination, task completion), support for local judge models and synthetic datasets, plus CI-friendly integrations for LangChain/OpenAI/Anthropic.
Runnable Jupyter notebooks for building with the Claude API: tool use, RAG, vision, prompt caching, sub-agents, classification, summarization, and integrations like Pinecone and Voyage embeddings. Copy-paste recipes that drop into real projects.
Awesome LLM Apps is a curated open-source repository collecting awesome LLM applications built with RAG, AI Agents, Multi-agent Teams, MCP, Voice Agents, and more, using models from OpenAI, Anthropic, Gemini, xAI, and open-source alternatives like Qwen or Llama that can run locally.
Builds stateful LLM agents whose memory persists across sessions: a tiered, self-editing memory system lets an agent rewrite its own context window so it remembers, learns, and improves over time. Model-agnostic, with Python/TypeScript SDKs.
Organizes reusable AI prompts as Markdown 'Patterns' you run from the CLI — summarize a video, extract claims, rate content. Switch among 20+ providers (OpenAI, Claude, Gemini, Ollama) and reach them via CLI, web UI, or REST API.