Coder CLI: An AI Coding Assistant That Lives in Your Terminal

Open Source Release | Role: Sole Developer & Maintainer

Coder CLI is an open-source, terminal-first AI coding assistant built in Go. It pairs a conversational agent with real developer tools — the filesystem, the shell, Git, task tracking, and a live view of the model's reasoning — all inside a keyboard-driven terminal interface. And because it speaks the Ollama API, it runs against any Ollama-compatible model, from a laptop running locally to a hosted GPU endpoint in the cloud.

The Three-Pane TUI

Most coding assistants hide the model's reasoning behind a spinner. Coder CLI makes it a first-class citizen. The interface is split into three live panes:

• Conversation — the transcript, with multi-line paste kept as a single message and GFM tables rendered as box-drawn tables.
• Cognition — a live stream of the model's reasoning, updated as it thinks.
• Activity — a running log of every tool the agent invokes and what it returns.

Seven Specialized Agents

Instead of one overstuffed persona, Coder CLI ships seven purpose-built agents, each with its own scoped toolset, system prompt, and default model. You swap between them with /agent — no restart, no context loss.

Any Ollama-Compatible Model

Coder CLI is provider-light by design. It speaks the Ollama API directly, which means it works with every model the Ollama ecosystem supports — Llama, Gemma, Qwen, MiniMax, Mistral, and beyond — whether that model is running on your own hardware or behind a remote endpoint.

• Local: point it at localhost:11434 and code entirely offline against a model running on your own machine.
• Cloud: pass --host to a remote Ollama-compatible endpoint and leverage hosted GPU acceleration.
• Gemini: a native Google Gemini provider is included for teams already on that stack.

Small-Model Reliability

A subtle but important detail: Coder CLI was built with the assumption that the model might be small. Its tool runner supports native tool-calls and a fenced-JSON fallback parser, so even a compact local model that fumbles the function-calling grammar can still reliably drive the filesystem and shell. That fallback is what makes the “works with any Ollama model” claim hold up in practice, not just in theory.

Beyond the Terminal

The agent's reach extends past the shell. A browser bridge drives a real Chrome instance over the Chrome DevTools Protocol — navigate, click, type, screenshot, and manage cookies and tabs across isolated profiles. It's what powers the social-researcher agent's ability to research Reddit and LinkedIn without ever repeating an upvote or message. Headless mode (coder -p "…") makes the same engine scriptable for CI pipelines, and an MCP client lets the agent reach third-party servers for tools it doesn't natively ship.

Install It in One Line

Distribution is deliberately frictionless — an npm package downloads the right prebuilt binary on install, and a one-line shell installer covers everything else, with an option to set up Ollama and pull a default model in the same step.

# npm
npm install -g @tjcoder/cli

# one-line installer (with optional Ollama setup)
INSTALL_OLLAMA=1 curl -fsSL \
  https://raw.githubusercontent.com/tjcoder-labs/cli/main/install.sh | bash

About the Author

TJ Coder AI Labs builds modern, AI-powered developer tooling — from autonomous agents to terminal-native interfaces — out of Las Vegas, Nevada. Coder CLI is open source under the MIT license and available on npm and GitHub.