OpenClaude: review, pricing, security and alternatives

What OpenClaude does

OpenClaude belongs to the coding agents family: they read a repository, edit files, run the tests and fix things until everything passes, in a terminal or an editor. On our grid it ranks #18 of the 74 projects of this family listed in the directory.

You use it from: terminal (CLI) and code editor (IDE). Usable models: GPT (OpenAI), Gemini (Google), local models (Ollama, llama.cpp, vLLM…), and any OpenAI-compatible model. It can run on your own machine or server.

Who is OpenClaude for?

It is aimed at developers and technical teams who want to hand off part of the work on their codebase while keeping the final review. Typical tasks people give it:

• fix a bug from an issue or an error message
• write or extend tests
• migrate code to a new library version
• explain an unfamiliar codebase

It is a good candidate if you are comfortable in a terminal, you want the AI right inside your code editor, your data must stay on your machines, and you want the option of a local model, with no API fees.

Access and human control

According to its documentation, OpenClaude can:

• run commands in a terminal
• read and edit files
• call online services and APIs

We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.

OpenClaude pricing

The code is public but the repository declares no licence: reuse is not formally allowed. The real cost comes from model calls: each loop step sends the whole context back to the model, and a task of several dozen steps can cost far more than a single question. The LLM price calculator estimates it for the chosen model.

Getting started with OpenClaude

1. Install it: the project ships as a Node.js package (install with npm, or run directly with npx). The exact command is in the repository README.
2. Pick the model: an API key from a provider, or a local model if your machine has enough graphics memory (the VRAM calculator tells you).
3. Give it a first playground with nothing at stake: a test folder, a secondary account or a throwaway project. Only open your real accounts once you have seen how it behaves.
4. Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.

Security: risk level

A coding agent runs commands on your machine: work on a Git branch, review the changes and isolate it in a container for long tasks.

Points found for OpenClaude:

• Sensitive access: it can run commands in a terminal, with no established default human approval.
• Outside content: it reads web pages or API responses, which may contain booby-trapped instructions (prompt injection).
• No licence: legally shaky for company use.

Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.

Project activity and releases

Created on April 1, 2026, the Twigpine/openclaude repository has 34,129 stars, 9,131 forks and 50 open issues, with 1,334 commits in total. It received changes this month.

Over the last 52 weeks: 1,229 commits, an average of 23.6 per week.

45 releases in total; 30 in the last twelve months. Latest release: v0.33.0, on October 15, 2026.

OpenClaude vs other coding agents

GitHub stars of the best-rated open-source projects in the coding agents family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.

OpenClaude and other coding agents at a glance

The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.

How we rated it

Score: 75/100, computed only from public, verifiable data, with no subjective testing or partnership:

• Adoption 30/40: 34,129 stars on a log scale (40 points from about 200,000).
• Activity 30/30: last commit less than a month ago, 30 releases in six months, 1,229 commits in a year.
• Framework 15/30: licence, default human approval, self-hosting, model choice and documentation site.

The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.