Meet OpenClaude: One Terminal for All Your AI Coding Models
If you've been following the AI coding scene, you've probably noticed a new CLI tool popping up every week. Some work great with OpenAI, others only with Anthropic, and a few are locked to a single cloud provider. OpenClaude wants to end that fragmentation. It's an open-source coding-agent CLI that brings cloud and local model providers together under one terminal-first workflow.
What Is OpenClaude?
OpenClaude is an open-source coding-agent CLI built for both cloud and local model providers. You can use OpenAI-compatible APIs, Gemini, GitHub Models, Codex OAuth, Codex, Ollama, Atomic Chat, and other supported backends — all with the same prompts, tools, agents, MCP, slash commands, and streaming output. No per-provider tooling required.
One important note: OpenClaude originated from Claude Code but has been substantially modified to support multiple providers. It's an independent community project, not affiliated with Anthropic. It also stores its own config under ~/.openclaude — it doesn't read ~/.claude or Claude Code credentials, so you start completely clean.
Get Started in Minutes
OpenClaude requires Node.js >= 22.0.0. Install it globally:
Then just run:
Inside the CLI, run /provider for guided provider setup, or /onboard-github for GitHub Models onboarding. The setup saves profiles and credentials in .openclaude-profile.json.
Want the fastest OpenAI setup? Set three environment variables:
Prefer local models? Point it at Ollama:
That's it. Same workflow, completely different model backend. On Arch Linux, you can even install it from the AUR: paru -S openclaude.
Which Providers Are Supported?
OpenClaude supports a long list of providers:
Each provider has a guided setup path through /provider, so you don't need to memorize every API shape.
What Can You Do With It?
OpenClaude isn't just a chat wrapper — it's a full coding-agent workflow:
Here's a quick example of background usage:
Route Agents to Different Models
One standout feature is agent routing. You can direct different agents to different models based on cost or capability, and cap sub-agent tool steps with maxSteps. For example, you can let a cheap model handle exploration tasks while a stronger model handles critical code reviews. Configure it all with agentModels and agentRouting in ~/.openclaude/settings.json.
Web Search and Fetch Built In
By default, WebSearch works on non-Anthropic models using DuckDuckGo, so GPT-4o, DeepSeek, Gemini, Ollama, and other OpenAI-compatible providers get a free web search path out of the box. If you need more reliable scraping for JavaScript-rendered sites, set a Firecrawl API key and OpenClaude will use Firecrawl's search and scrape endpoints instead.
Headless gRPC Server for Custom Integrations
Want to embed OpenClaude into your own app or CI/CD pipeline? It can run as a headless gRPC service with bidirectional streaming. Start it with npm run dev:grpc and generate clients from src/proto/openclaude.proto. That's a very handy escape hatch for teams building custom UIs or automation around an agentic core.
VS Code Extension Included
The repo includes a VS Code extension with launch integration, a provider-aware Control Center, in-editor chat, and theme support. It even supports optional Microsoft Foundry / Azure OpenAI configuration, injecting endpoint, deployment, and API key settings into launched terminals.
Oh, and You Get a Pixel-Art Buddy
This is the part that makes OpenClaude memorable. Run /buddy to hatch a truecolor pixel-art hero who lives next to your prompt, idles, blinks, and fires a signature move every time you press Enter. You can choose your fighter:
Companions respect prefersReducedMotion, degrade gracefully to line art in low-color terminals, and can be muted with /buddy mute. Honestly, it makes coding in the terminal feel a little more alive.
Should You Try It?
If you're tired of juggling multiple AI CLI tools — or you want a consistent workflow whether you're using a cloud model like GPT-4o or a local model like qwen2.5-coder — OpenClaude is worth a spin. It's open source, MIT-licensed, actively maintained, and has a friendly community on Discord and GitHub Discussions.
One thing to keep in mind: not every provider behaves identically. Anthropic-specific features may not exist on other backends, tool quality depends heavily on the model you pick, and smaller local models can struggle with long multi-step tool flows. Use models with strong tool/function calling support for the best results.
Install it in one line, run /provider, and see how nice it is to have one terminal for every LLM.
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