nanocode-cli 0.9.1

A small terminal coding agent written in Python

nanocode-cli

A coding agent I use, maintain, and customize in one Python file.

_{Editing code and running tools in one interactive session.}

中文

Install

Requires Python 3.11+ and uv.

uv tool install nanocode-cli
nanocode --init-config

Configure any OpenAI-compatible provider in ~/.nanocode/config.toml. For example, DeepSeek Flash:

[provider]
active = "default"

[provider.default]
url = "https://api.deepseek.com"
key = "API_KEY"
model = "deepseek-v4-flash"

Replace url, key, and model with the values from your provider.

Then start:

nanocode

Upgrade: nanocode upgrade

Common flags:

• --resume [UID]: resume a saved session; without UID, resumes latest
• --yolo: skip tool confirmations
• --mcp <selector>: choose which MCP servers to enable
• --config <path>: use a specific TOML config file

A working personal agent

nanocode does not introduce a new kind of coding agent. It combines familiar features—reading and editing files, running commands, follow-ups, sessions, diffs, MCP, and skills—into a tool I use personally.

It works on real repositories, including its own: I use nanocode to build and maintain nanocode. Everything ships in one Python module, so I can change the behavior directly whenever I want the workflow to work differently.

_{Resuming a saved session with its conversation and tool history.}

Highlights

• Live follow-ups: type while the agent works; queued input joins the next model request or can interrupt the current one.
• Anchored edits: structured edits use line:hash anchors and reject stale file content instead of guessing.
• Resumable sessions: conversation, completed tool calls, diffs, and working memory survive interruption and --resume.
• Built-in diff viewer: /diff shows changes from the latest user round and the net session result.
• Prompt-cache aware: stable instructions, environment, and tool schemas preserve reusable request prefixes.
• Provider compatibility: tested with DeepSeek, OpenCode, Alibaba Cloud, and ZenMux; other OpenAI-compatible endpoints should work in principle. Anthropic APIs, remote/local MCP servers, and Markdown skills are also supported.

Common commands

Command	Description
/help	Show the complete command and tool reference
/status	Runtime status: token usage, context %, cache hit rate
/context	Model context frame — environment and memory (goal/plan/known/check)
/diff	Latest edit diffs and net session diff (interactive, tabbed)
/compact	Compact context now
/mcp	Manage MCP servers and tools
/model [MODEL]	Show or switch model
/yolo	Toggle tool confirmations

Run /help for every command, tool, and shortcut. Interactive selectors support j/k, arrows, / search, Enter, and Esc; input supports history completion and Ctrl-R search.

Configuration

Config file: ~/.nanocode/config.toml

The generated file documents common provider and runtime options. Multiple [provider.<name>] sections are supported; select one with [provider] active = "name". Use /config to inspect the active configuration and /help for runtime commands.

MCP

Connect to Model Context Protocol servers and expose their tools through MCP.

Remote server (HTTP):

[mcp.example]
url = "https://example.com/mcp"
bearer_token_env_var = "EXAMPLE_MCP_TOKEN"  # optional
enabled = true

Local server (stdio):

[mcp.filesystem]
command = "npx"
args = ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"]
enabled = true

Runtime management: /mcp to view status, /mcp tools [server] to list tools, /mcp login/logout <server> for OAuth.

Skills

Skills are instruction packs the agent loads on demand. Each skill is a folder with a SKILL.md.

• Discovery: .nanocode/skills/ (project) and ~/.nanocode/skills/ (user); project wins on name clash
• Model view: only a name + description index sits in context; the full body loads on Skill(name) call
• Inline reference: type $name in a message (Tab-completes) to inject that skill's instructions
• Bundled scripts: {skill_dir} expands to the skill's absolute path for running via Bash
• Built-in: ships with a nanocode-help skill containing a self-contained manual and auto-generated command/tool/config lists

Safety

Use at your own risk. nanocode can edit files and run shell commands in the environment where it is started. It does not provide sandbox protection. Run it inside your own sandbox, container, VM, or other isolated environment when needed.