claw-code vs pi
Two of the top projects in Coding agents and assistants, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
claw-code
Rust CLI coding agent harness using Anthropic and OpenAI-compatible APIs
pi
Terminal coding agent with extensions, skills, and an SDK
Verdict
claw-code ranks higher, 83 to 79. Of the 5 score parts we measure for both, claw-code leads on 3, pi on none and 2 are even.
- Adoptionclaw-code leads by 4 points, 98 to 94: close to even.
- FreshnessEven at 100.
- Maintenanceclaw-code leads by 2 points, 99 to 97: close to even.
- Easy to runEven at 50.
- Agent-readyclaw-code leads by 40 points, 70 to 30: a wide gap.
Pick claw-code if you are
Developers who want to inspect or build a Rust CLI coding agent
- `claw doctor` checks API key, model access and tool configuration after build
- Docs cover local OpenAI-compatible providers: Ollama, llama.cpp, vLLM
Pick pi if you are
Developers who want a scriptable, customizable terminal coding agent
- Multiple interfaces: interactive CLI, print/JSON mode, RPC and a TypeScript SDK
- Extensions, skills, prompt templates and themes ship as npm or git packages
| What we compare | claw-code | pi |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 98, widely used | 94, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 99, healthy | 97, healthy |
| Easy to run | 50, easy | 50, easy |
| Agent-ready | 70, partly | 30, minimal |
| Facts from GitHub and the README | ||
| Stars | 194.9k | 115.2k |
| License | MIT (permissive) | MIT (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Rust | TypeScript |
| Docker | Yes | No |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Mentioned | Mentioned |
claw-code
Claw Code is a Rust implementation of the `claw` command-line coding agent, built from source with cargo. It runs one-shot prompts or interactive sessions using an API key, and the docs cover local OpenAI-compatible servers such as Ollama, llama.cpp and vLLM. The README describes the repo as an agent-managed exhibit, not the production project, and points to LazyCodex and Gajae-Code for real work.
Who it is for: Developers who want to inspect or build a Rust CLI coding agent
Strengths
- `claw doctor` checks API key, model access and tool configuration after build
- Docs cover local OpenAI-compatible providers: Ollama, llama.cpp, vLLM
- Build steps documented for macOS, Linux and Windows PowerShell
- MIT license; workspace test suite and deterministic mock-service parity harness
Weaknesses
- README says it is not the serious production project and points elsewhere
- Build-from-source only; `cargo install claw-code` installs a deprecated stub
- Requires an API key; Claude subscription login is not supported
- No ACP/Zed daemon yet; `claw acp serve` only returns status
- no GPU
- Docker + Compose
- Needs Rust toolchain (cargo), LLM API key
- Models: Anthropic API, OpenAI-compatible APIs, Ollama, llama.cpp, vLLM
pi
Pi is a TypeScript coding agent CLI that runs in your project directory and connects to LLM providers through a login or API key. It is customized with extensions, skills, prompt templates and themes, shared as npm or git packages, and can be driven interactively, in print/JSON mode, over RPC, or through a TypeScript SDK. The monorepo also ships a multi-provider LLM API, an agent runtime and a terminal UI library.
Who it is for: Developers who want a scriptable, customizable terminal coding agent
Strengths
- Multiple interfaces: interactive CLI, print/JSON mode, RPC and a TypeScript SDK
- Extensions, skills, prompt templates and themes ship as npm or git packages
- Core libraries (pi-ai, pi-agent-core, pi-tui) are published as separate packages
- Installer pins dependencies; Nix flake builds on Linux and macOS, ARM64 and x86-64
Weaknesses
- No built-in permission system; runs with the launching user's full permissions
- Sub-agents and plan mode are intentionally omitted and must be added via packages
- Requires Node.js 22.19 or newer
- New contributors' issues and PRs are auto-closed by default
- no GPU
- Needs Node.js 22.19+, LLM provider API key or subscription
- Models: OpenAI, Anthropic, Google
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