What Is Claude AI and What Can You Do With It?

Updated

Claude AI is Anthropic's family of large language models, accessed through a chat interface or, for developers, through the Claude API, official SDKs, and cloud providers such as Amazon Bedrock. You can use it to read and analyze long documents, write and review code, and build tool-using agents — but the right entry point depends on whether you want to chat with Claude or build with it. The sections below cover both, plus the concepts (MCP, agent skills, prompt caching) you'll meet once you start building.

Who makes Claude and what the model family includes

Claude is developed by Anthropic. The model lineup referenced in Anthropic's documentation covers several tiers — the Awesome Claude directory lists Fable 5.1, Opus 5.5, Sonnet 5.5, and Haiku 4.5 among the models available through Amazon Bedrock. In practice, the tiers trade off capability against speed and cost: the larger models handle harder reasoning and coding tasks, while the smaller ones suit high-volume or latency-sensitive work. Anthropic's models overview page is the authoritative place to check current model IDs, context windows, thinking features, and cloud provider IDs before you commit to one.

Core capabilities

  • Chat and long-document analysis. Claude's context window lets you pass in substantial source material — contracts, research papers, codebases — and ask questions against it rather than pasting excerpts.
  • Coding. Claude Code is Anthropic's coding-focused product; the directory also tracks a Claude Code 2.1 cheatsheet for developers working with it.
  • Tool use and computer use. The Messages API supports tool use (letting the model call functions you define) and computer use, alongside structured outputs, citations, and prompt caching.
  • Agent building. The Agent SDK (Python and TypeScript) is designed for constructing agents that plan and act across multiple steps.

How developers access Claude

There are three main routes, and they differ in what you control:

Route What you get When it fits
Claude Developer Console (console.anthropic.com) API keys, prompt testing, usage monitoring, Claude Code sessions Getting started, testing prompts, managing keys
Official SDKs Python, TypeScript/JavaScript, Java/Kotlin, Go, Ruby, C#/.NET (Beta), PHP (Beta) Building applications in your language of choice
Amazon Bedrock Fully managed access to Claude models via the Messages-API Bedrock endpoint, with cross-region inference, latency optimizations, fine-tuning, agents, guardrails, and AWS integration You're already on AWS and want managed infrastructure

One caveat worth knowing before you pick Bedrock: per the directory's note, Managed Agents and Anthropic server-side tools are not available there — you'd use the Claude API with tool use instead. Bedrock model IDs also take a prefix and are served through the Messages-API endpoint, so code written against the direct API needs that adjustment.

Key concepts for building with Claude

MCP (Model Context Protocol) is the standard for connecting Claude to external tools and data sources; the directory maintains a list of top MCP servers. Agent skills are reusable capabilities you attach to an agent rather than re-prompting each time. Prompt caching reduces cost and latency on repeated context — useful when the same long document or system prompt is sent across many requests. If you're new to these, the official Claude Cookbook (53.4k stars) has notebooks covering RAG, tool use, Skills, and MCP, and Claude Quickstarts (18.0k stars) provides deployable example apps.

Where to start

  1. Read the docs first. platform.claude.com/docs is the full reference for the Messages API, tool use, computer use, prompt caching, structured outputs, citations, MCP Connector, and Claude Code.
  2. Check models and pricing. The models overview page lists model IDs, pricing, context windows, and thinking features — confirm current figures there rather than relying on secondhand numbers.
  3. Get a key and test a prompt. Create one in the Developer Console, then run a small request to confirm your setup before scaling up.
  4. Pick an SDK matching your stack and work through a Cookbook notebook for the pattern closest to your use case.
  5. Verify your first integration by checking that responses return as expected and that usage appears in the console's monitoring.

A common snag is assuming Bedrock and the direct API behave identically — check the endpoint and model-ID format before porting code. Another is skipping prompt caching on repetitive workloads, which quietly inflates cost.

For a broader map of the ecosystem — plugins, integrations, and community-curated lists — the Awesome Claude directory is a reasonable index, but treat it as a pointer to official sources rather than a substitute for them.