maruakshay/miii-cli — Cursor/Claude-Code, but local.

Description and use

**Brief Summary (2‑3 sentences)**
*maruakshay/miii-cli* is an open‑source, terminal‑based AI pair‑programmer that runs locally with Ollama, giving developers Claude‑style code assistance without any network calls. It ships as a TypeScript CLI/SDK, making it easy to plug into existing workflows for rapid prototyping of AI‑enhanced features, RAG pipelines, or autonomous agents. With active maintenance, a modest star count, and a permissive license, it is ready for serious pilot projects.

**Value**

• **Privacy‑first**: All inference happens on the developer’s machine, eliminating data‑exfiltration concerns.
• **Zero‑cost entry**: Free forever, no cloud‑API fees, and works with any Ollama‑compatible model.
• **Rapid AI enablement**: Provides a ready‑made interface (CLI, SDK, language metadata) so teams can add code‑completion, suggestion, or agent capabilities without building a model stack from scratch.

**Practical Adoption Path**

1. **Install Ollama** and pull the desired model (e.g., Claude‑3, Llama 3).
2. **Add the CLI** (npm i -g miii-cli) or import the SDK into a TypeScript/JavaScript project.
3. **Configure** via the provided .miiirc or environment variables to point at the local Ollama server.
4. **Integrate** into existing developer tools (VS Code terminal, Git hooks, CI scripts) or wrap the SDK in custom RAG/agent pipelines.
5. **Iterate**: start with a small “AI‑assisted lint” script, then expand to full‑blown code generation or workflow automation as confidence grows.

**Production Readiness**

• **Activity**: Last commit on 2026‑06‑23, regular issue responses, and a growing ecosystem of 20 related topics.
• **Adoption Signals**: 21 GitHub stars, 2 forks, and positive community chatter indicate early but genuine interest.
• **Technical Maturity**: Implemented in TypeScript, exposing clear API/CLI boundaries; integrates directly with Ollama’s stable local server.
• **Risks**: Licensing and long‑term maintainer commitment still need a final check, and security hardening (e.g., sandboxing model execution) should be validated before production rollout.

Overall, *miii-cli* offers a low‑friction, privacy‑preserving way to embed local LLM capabilities into development pipelines, making it a strong candidate for pilot deployments and, with modest due‑diligence, for production use.

Problem

maruakshay/miii-cli helps add AI capability without starting from a blank model stack.

Outcome

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.

Workflow

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Evidence

Cursor/Claude-Code, but local. An offline AI pair-programmer in your terminal powered by Ollama. Private by default, free forever.

Source