nclaw

NClaw — aNother Claw. A lightweight, container-first AI coding assistant accessible through Telegram. Supports Claude Code (default), 580+ models via multi-model backend (OpenRouter, Gemini, OpenAI, Ollama, and more), OpenAI Codex, GitHub Copilot, and Google Gemini CLI as CLI agents. Written in Go.

Why NClaw

There are many AI assistants already — OpenClaw, NanoClaw, ClaudeClaw, and others. NClaw exists because none of them satisfied three requirements at once:

Container-first. NClaw is built to run in Docker and Kubernetes from day one. The repo ships a multi-stage Dockerfile and a Helm chart. No manual setup, no runtime dependency resolution — docker run or helm install and you're done.

Lightweight. A single Go binary. Idles at ~10 MB of RAM. No runtime interpreter, no package manager overhead, no garbage collection pauses that matter.

Telegram topics as projects. NClaw treats each Telegram topic (thread) as a separate session with its own working directory. One group chat with topics becomes a multi-project workspace — each topic gets isolated context, history, and files.

How It Works

You message the assistant through Telegram. It invokes the configured CLI agent (Claude Code by default), preserving conversation history per chat/topic, and sends back the response.

Telegram  -\
Scheduler -->  CLI Backend  -->  Telegram
Webhook   -/

The recommended way to run NClaw is inside Docker — the container serves as a security sandbox, and the image ships with all the tools the assistant might need. However, NClaw is a regular executable and can run directly on any machine with the chosen CLI agent installed.

Features

Session persistence — Each chat/topic maintains its own session. Pick up where you left off.
Telegram topics — Each topic in a group chat is a separate project with isolated context and files.
File attachments — Send photos, documents, audio, video to the assistant.
File delivery — The assistant can send files back to you (generated reports, exports, code).
Scheduled tasks — Create recurring or one-time jobs using natural language.
Webhooks — Register HTTP endpoints that forward incoming requests to the assistant in your chat.
Rich runtime — Docker image includes git, gh CLI, Chromium, Go, Node.js, Python/uv. The assistant can install additional packages on the fly as needed — for example, apk add ffmpeg to process video, npm install -g prettier to format code, or pip install pandas to analyze data.
Multiple CLI agents — Supports Claude Code (default), multi-model (580+ models via OpenRouter, Gemini, OpenAI, Ollama, etc.), OpenAI Codex, GitHub Copilot, and Google Gemini CLI. Switch agents via the NCLAW_CLI environment variable.
HTML-formatted replies — Responses render using Telegram's HTML formatting with plain-text fallback.

Quickstart

Get NClaw running in under 5 minutes using Docker.

Step 1: Create a Telegram Bot

Open Telegram and search for @BotFather (or open t.me/BotFather).
Send /newbot.
Choose a display name for your bot (e.g. "My Coding Assistant").
Choose a username — must end in bot (e.g. my_coding_assistant_bot).
BotFather replies with your bot token — a string like 123456789:ABCdefGhIjKlMnOpQrStUvWxYz. Save it.

Tip: You can customize the bot later — send /mybots to BotFather to change the name, description, profile picture, and more.

If you want the bot in a group with topics (one topic per project), also configure these via BotFather:

Send /mybots → select your bot → Bot Settings → Group Privacy → Turn off. This lets the bot read all messages in group chats, not just commands.
Send /setjoingroups → select your bot → Enable. This allows adding the bot to groups.

Step 2: Find Your Chat ID

NClaw uses NCLAW_TELEGRAM_WHITELIST_CHAT_IDS to restrict which chats the bot responds in. This setting is optional, but strongly recommended — without it, anyone who discovers your bot can send it commands with full access to the container's file system, shell, and network. You need the numeric chat ID.

For a private chat (1-on-1 with the bot):

Message your bot (send anything — it won't reply yet).
Open this URL in a browser, replacing <TOKEN> with your bot token:
```
https://api.telegram.org/bot<TOKEN>/getUpdates
```
Find "chat":{"id":123456789} in the JSON response. That number is your chat ID.

For a group chat:

Add the bot to the group.
Send a message in the group.
Use the same getUpdates URL above. The group chat ID is a negative number (e.g. -1001234567890).

Tip: You can whitelist multiple chat IDs by separating them with commas: 123456789,-1001234567890.

Step 3: Run NClaw

The fastest way to get started is with the multi-model image using a free Gemini API key:

Get a free API key from Google AI Studio.

Run:

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-bot-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -e NCLAW_MODEL=g@gemini-2.5-pro \
  -e GEMINI_API_KEY=your-gemini-key \
  -v ./data:/app/data \
  ghcr.io/nickalie/nclaw:multi-model

Message your bot in Telegram — it should reply.

To use Claude Code instead (requires an Anthropic account with Claude Code access):

Install Claude Code and authenticate:

curl -fsSL https://claude.ai/install.sh | bash
claude login

Run:

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-bot-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -v ./data:/app/data \
  -v ~/.claude/.credentials.json:/root/.claude/.credentials.json:ro \
  ghcr.io/nickalie/nclaw:claude

See Docker for all image variants and Configuration for the full list of options.

Docker

NClaw provides six Docker images, all based on node:24-alpine with shared tools (git, gh CLI, Chromium, Go, Node.js, Python/uv, skills). They differ only in which CLI agent is pre-installed:

Image	Tag	CLI Backends	Size
All-in-one	`latest`	Claude Code + Multi-Model + Codex + Copilot + Gemini	Largest
Claude	`claude`	Claude Code	Medium
Multi-Model	`multi-model`	Claude Code + Multi-Model	Medium
Codex	`codex`	OpenAI Codex	Medium
Copilot	`copilot`	GitHub Copilot	Medium
Gemini	`gemini`	Google Gemini CLI	Medium

All images are published to ghcr.io/nickalie/nclaw and built for linux/amd64 and linux/arm64. Docker automatically pulls the correct architecture — no extra flags needed. This means you can run NClaw on:

Raspberry Pi (4/5 or any arm64 board) — a dedicated AI coding assistant on a $35 device
AWS Graviton instances — lower cost and better price-performance than x86
Apple Silicon Macs — native arm64 without Rosetta emulation
Oracle Cloud Ampere or any other arm64 cloud VM

The assistant can install additional packages at runtime (e.g. apk add ffmpeg, pip install pandas, npm install -g typescript).

Claude (default)

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -v ./data:/app/data \
  -v ~/.claude/.credentials.json:/root/.claude/.credentials.json:ro \
  ghcr.io/nickalie/nclaw:claude

Claude Code uses OAuth authentication. Mount your credentials file from ~/.claude/.credentials.json. To obtain credentials, install Claude Code locally and run claude login.

Multi-Model

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -e NCLAW_MODEL=g@gemini-2.5-pro \
  -e GEMINI_API_KEY=your-gemini-key \
  -v ./data:/app/data \
  ghcr.io/nickalie/nclaw:multi-model

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -e NCLAW_MODEL=zai@glm-4 \
  -e ZAI_API_KEY=your-zai-key \
  -v ./data:/app/data \
  ghcr.io/nickalie/nclaw:multi-model

Setting NCLAW_MODEL automatically selects the multi-model backend. No Anthropic credentials are needed — only an API key from your chosen provider. See Multi-Model for full configuration details.

Codex

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -e NCLAW_CLI=codex \
  -v ./data:/app/data \
  -v ~/.codex/auth.json:/root/.codex/auth.json:ro \
  ghcr.io/nickalie/nclaw:codex

Codex uses ChatGPT OAuth authentication. Mount your auth file from ~/.codex/auth.json. To obtain credentials, install Codex locally (npm install -g @openai/codex) and sign in on first run.

Copilot

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -e NCLAW_CLI=copilot \
  -v ./data:/app/data \
  -v ~/.copilot/config.json:/root/.copilot/config.json:ro \
  ghcr.io/nickalie/nclaw:copilot

Copilot uses GitHub OAuth authentication. Mount your config file from ~/.copilot/config.json. To obtain credentials, install Copilot CLI locally (npm install -g @githubnext/github-copilot-cli) and run /login.

Gemini

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -e NCLAW_CLI=gemini \
  -v ./data:/app/data \
  -v ~/.gemini/oauth_creds.json:/root/.gemini/oauth_creds.json:ro \
  ghcr.io/nickalie/nclaw:gemini

Gemini CLI uses Google account OAuth authentication. Mount your credentials file from ~/.gemini/oauth_creds.json. To obtain credentials, install Gemini CLI locally (npm install -g @google/gemini-cli) and sign in on first run.

All-in-one

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -v ./data:/app/data \
  -v ~/.claude/.credentials.json:/root/.claude/.credentials.json:ro \
  ghcr.io/nickalie/nclaw:latest

The all-in-one image includes all five CLI agents. Set NCLAW_CLI to claude (default), claudish (multi-model), codex, copilot, or gemini to choose the agent. Mount the appropriate credentials for your chosen agent.

Webhooks

To enable webhooks, add the webhook base domain and expose the port:

docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -e NCLAW_WEBHOOK_BASE_DOMAIN=example.com \
  -e NCLAW_WEBHOOK_PORT=:3000 \
  -p 3000:3000 \
  -v ./data:/app/data \
  -v ~/.claude/.credentials.json:/root/.claude/.credentials.json:ro \
  ghcr.io/nickalie/nclaw:latest

Multi-Model

NClaw's multi-model backend (powered by claudish) lets you use 580+ models from OpenRouter, Google Gemini, OpenAI, Vertex AI, Ollama, LM Studio, and more — while retaining full agentic capabilities (tool use, file editing, scheduled tasks, webhooks, file delivery).

Supported Providers

Provider	Prefix	Example	Auth
OpenRouter	`or@`	`or@deepseek/deepseek-r1`	`OPENROUTER_API_KEY`
Google Gemini	`g@`	`g@gemini-2.0-flash`	`GEMINI_API_KEY`
OpenAI	`oai@`	`oai@o3-mini`	`OPENAI_API_KEY`
Vertex AI	`v@`	`v@gemini-2.5-flash`	`VERTEX_API_KEY`
OllamaCloud	`oc@`	`oc@llama-3.1-70b`	`OLLAMA_API_KEY`
Kimi	`kimi@`	`kimi@kimi-k2`	`MOONSHOT_API_KEY`
GLM (Zhipu)	`glm@`	`glm@glm-4`	`ZHIPU_API_KEY`
Z.AI	`zai@`	`zai@glm-4`	`ZAI_API_KEY`
MiniMax	`mm@`	`mm@MiniMax-M2.1`	`MINIMAX_API_KEY`
Poe	`poe@`	`poe@GPT-4o`	`POE_API_KEY`
OpenCode Zen	`zen@`	`zen@grok-code`	Free (no key)
Gemini CodeAssist	`go@`	`go@gemini-2.5-flash`	OAuth
Ollama	`ollama@`	`ollama@llama3.2`	Local (no key)
LM Studio	`lms@`	`lms@qwen2.5-coder`	Local (no key)
vLLM	`vllm@`	`vllm@mistral-7b`	Local (no key)
MLX	`mlx@`	`mlx@llama-3.2-3b`	Local (no key)

Well-known model names (e.g. gemini-2.0-flash, llama-3.1-70b) are auto-detected without a provider prefix.

Model Selection

Set NCLAW_MODEL to choose the default model. This automatically selects the multi-model backend — no need to set NCLAW_CLI explicitly:

# Use Gemini via direct API
docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -e NCLAW_MODEL=g@gemini-2.5-pro \
  -e GEMINI_API_KEY=your-key \
  -v ./data:/app/data \
  ghcr.io/nickalie/nclaw:multi-model

# Use GLM-4 via Z.AI
docker run -d --name nclaw \
  -e NCLAW_MODEL=zai@glm-4 \
  -e ZAI_API_KEY=your-key \
  ...

# Use any model via OpenRouter
docker run -d --name nclaw \
  -e NCLAW_MODEL=or@mistralai/mistral-large \
  -e OPENROUTER_API_KEY=your-key \
  ...

# Use a local model via Ollama
docker run -d --name nclaw \
  -e NCLAW_MODEL=ollama@llama3.2 \
  ...

Local Models

For fully offline operation, use Ollama or LM Studio. Your code never leaves your machine:

# Start Ollama and pull a model
ollama pull llama3.2

# Run nclaw with a local model
docker run -d --name nclaw \
  -e NCLAW_TELEGRAM_BOT_TOKEN=your-token \
  -e NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id \
  -e NCLAW_DATA_DIR=/app/data \
  -e NCLAW_MODEL=ollama@llama3.2 \
  -e OLLAMA_BASE_URL=http://host.docker.internal:11434 \
  -v ./data:/app/data \
  ghcr.io/nickalie/nclaw:multi-model

Set OLLAMA_BASE_URL, LMSTUDIO_BASE_URL, VLLM_BASE_URL, or MLX_BASE_URL to connect to custom endpoints.

Kubernetes (Helm)

The Helm chart is published as an OCI artifact to GHCR. Since all Docker images are multi-arch (amd64/arm64), the chart works on mixed-architecture clusters — including AWS Graviton node pools, Raspberry Pi k3s clusters, and Apple Silicon dev machines.

helm install nclaw oci://ghcr.io/nickalie/charts/nclaw \
  --set env.telegramBotToken=your-token \
  --set env.whitelistChatIds=your-chat-id \
  --set claudeCredentialsSecret=my-claude-secret

Create the credentials secret for your chosen agent:

# Claude
kubectl create secret generic my-claude-secret \
  --from-file=credentials.json=$HOME/.claude/.credentials.json

# Codex
kubectl create secret generic my-codex-secret \
  --from-file=auth.json=$HOME/.codex/auth.json

# Copilot
kubectl create secret generic my-copilot-secret \
  --from-file=config.json=$HOME/.copilot/config.json

# Gemini
kubectl create secret generic my-gemini-secret \
  --from-file=oauth_creds.json=$HOME/.gemini/oauth_creds.json

Helm values

Parameter	Default	Description
`image.repository`	`ghcr.io/nickalie/nclaw`	Docker image
`image.tag`	Chart appVersion	Image tag
`env.dataDir`	`/app/data`	Data directory inside container
`env.telegramBotToken`	`""`	Telegram bot token
`env.whitelistChatIds`	`""`	Comma-separated allowed chat IDs
`env.webhookBaseDomain`	`""`	Base domain for webhook URLs
`env.cli`	`""`	CLI agent: `claude`, `claudish` (multi-model), `codex`, `copilot`, or `gemini` (empty = image default)
`env.model`	`""`	Model for multi-model backend (e.g. `g@gemini-2.5-pro`). Setting this auto-selects multi-model
`existingSecret`	`""`	Use existing secret for bot token (key: `telegram-bot-token`)
`claudeCredentialsSecret`	`""`	Secret with Claude credentials (key: `credentials.json`)
`codexCredentialsSecret`	`""`	Secret with Codex credentials (key: `auth.json`)
`copilotCredentialsSecret`	`""`	Secret with Copilot credentials (key: `config.json`)
`geminiCredentialsSecret`	`""`	Secret with Gemini credentials (key: `oauth_creds.json`)
`persistence.enabled`	`true`	Enable persistent storage
`persistence.size`	`1Gi`	PVC size
`persistence.storageClass`	`""`	Storage class
`persistence.existingClaim`	`""`	Use existing PVC
`rbac.create`	`true`	Create ServiceAccount and ClusterRoleBinding
`rbac.clusterRole`	`cluster-admin`	ClusterRole to bind
`proxy.enabled`	`false`	Enable HTTP proxy
`proxy.httpProxy`	`""`	HTTP_PROXY value
`proxy.httpsProxy`	`""`	HTTPS_PROXY value
`resources.requests.cpu`	`100m`	CPU request
`resources.requests.memory`	`128Mi`	Memory request
`resources.limits.cpu`	`1000m`	CPU limit
`resources.limits.memory`	`2Gi`	Memory limit

Running without Docker

NClaw is a regular executable and can run directly on any machine. The only runtime dependency is the CLI for your chosen agent — Claude Code (default), claudish (multi-model), OpenAI Codex, GitHub Copilot, or Gemini CLI — it must be installed and available in PATH.

Security notice: Without Docker, the CLI agent runs directly on the host with the same permissions as the nclaw process. It has full access to the file system, network, and any credentials available to the user. Run under a dedicated unprivileged user and avoid running as root. For production use, Docker or Kubernetes deployment is strongly recommended.

Installation

Homebrew (macOS/Linux)

brew install --cask nickalie/apps/nclaw

Scoop (Windows)

scoop bucket add nickalie https://github.com/nickalie/scoop-bucket
scoop install nclaw

Chocolatey (Windows)

choco install nclaw

Winget (Windows)

winget install nickalie.nclaw

AUR (Arch Linux)

yay -S nclaw-bin

DEB / RPM / APK

Download the appropriate package from the Releases page:

# Debian/Ubuntu
sudo dpkg -i nclaw_*.deb

# Fedora/RHEL
sudo rpm -i nclaw_*.rpm

# Alpine
sudo apk add --allow-untrusted nclaw_*.apk

Binary download

Pre-built binaries for Linux, macOS, and Windows (amd64/arm64) are available on the Releases page.

Go install

CGO_ENABLED=1 go install github.com/nickalie/nclaw/cmd/nclaw@latest

Requires Go 1.25+ and a C compiler (CGO is needed for SQLite).

Usage

Install Claude Code CLI and authenticate:

curl -fsSL https://claude.ai/install.sh | bash
claude login

Create a .env file or export environment variables:

export NCLAW_TELEGRAM_BOT_TOKEN=your-token
export NCLAW_TELEGRAM_WHITELIST_CHAT_IDS=your-chat-id
export NCLAW_DATA_DIR=./data

Run:
```
nclaw
```

Any tools you want the assistant to use (git, gh, python, etc.) should be installed on the host. The assistant will use whatever is available in the system PATH.

Configuration

NClaw reads configuration from environment variables, .env files, or YAML config files.

Environment variables

NClaw variables use the NCLAW_ prefix. Provider API keys use the provider's native env var name (no prefix) — they pass through to the multi-model backend automatically.

Variable	Required	Default	Description
`NCLAW_TELEGRAM_BOT_TOKEN`	Yes	—	Telegram bot token from @BotFather
`NCLAW_DATA_DIR`	Yes	—	Base directory for session data and files
`NCLAW_CLI`	No	`claude`	CLI agent: `claude`, `claudish` (multi-model), `codex`, `copilot`, or `gemini`. Auto-selects `claudish` when `NCLAW_MODEL` is set
`NCLAW_MODEL`	No	—	Model for multi-model backend (e.g. `g@gemini-2.5-pro`). Setting this auto-selects multi-model
`NCLAW_TELEGRAM_WHITELIST_CHAT_IDS`	No	—	Comma-separated list of allowed Telegram chat IDs. If unset, accepts all chats (with a security warning)
`NCLAW_DB_PATH`	No	`{data_dir}/nclaw.db`	Path to the SQLite database
`NCLAW_TIMEZONE`	No	system local	Timezone for the scheduler (e.g. `Europe/Berlin`)
`NCLAW_WEBHOOK_BASE_DOMAIN`	No	—	Base domain for webhook URLs (required when using webhooks)
`NCLAW_WEBHOOK_PORT`	No	`:3000`	Webhook HTTP server listen address

Security notice: If NCLAW_TELEGRAM_WHITELIST_CHAT_IDS is not set, the assistant will accept messages from any Telegram chat. Since NClaw runs the CLI agent with full tool access (file system, shell, network), this effectively gives anyone who discovers your bot unrestricted access to the host environment. Always set this variable in production.

Config file

NClaw looks for config.yaml in the current directory or $HOME/.nclaw/. Nested keys map to env vars with underscores (e.g. telegram.bot_token = NCLAW_TELEGRAM_BOT_TOKEN).

telegram:
  bot_token: "your-telegram-bot-token"
  whitelist_chat_ids: "123456789,987654321"

cli: "claude"  # Options: claude, claudish, codex, copilot, gemini
data_dir: "/app/data"
db_path: "/app/data/nclaw.db"
timezone: "Europe/Berlin"

# Multi-model settings (setting model auto-selects multi-model backend)
model: ""                  # e.g. "g@gemini-2.5-pro", "or@mistralai/mistral-large"
# Provider API keys are set as regular env vars (not in this file):
# OPENROUTER_API_KEY, GEMINI_API_KEY, OPENAI_API_KEY, etc.

webhook:
  base_domain: "example.com"
  port: ":3000"

Scheduling

Talk naturally to create scheduled tasks:

Remind me to take a break every 2 hours
Every morning at 8am, give me a weather summary and top news headlines
At 3pm today, generate a summary of today's git commits

Tasks persist across restarts. Each task can either continue the existing chat session or run in a fresh isolated context.

Webhooks

Register HTTP endpoints that forward incoming requests to the assistant:

Create a webhook that receives GitHub push events and summarizes the changes
Set up a webhook for my package tracking updates
Listen for smart home alerts and notify me about unusual activity

When an external service calls the webhook URL, the request (method, headers, query params, body) is forwarded to the assistant in the originating chat. The HTTP endpoint returns 200 immediately; the assistant processes the request asynchronously. Webhooks persist across restarts.

Requires NCLAW_WEBHOOK_BASE_DOMAIN to be set. Webhook URLs follow the pattern https://{BASE_DOMAIN}/webhooks/{UUID}.

Skills

Six skills ship with nclaw:

Skill	Source	Purpose
`schedule`	Custom	Create and manage scheduled tasks via natural language
`send-file`	Custom	Send generated files back to the user via Telegram
`webhook`	Custom	Register HTTP endpoints that forward requests to the assistant
`find-skills`	vercel-labs/skills	Discover and install additional agent skills
`skill-creator`	anthropics/skills	Guide for creating new custom skills
`agent-browser`	vercel-labs/agent-browser	Browse the web using system Chromium

The assistant can also create its own skills on the fly when a task requires specialized or repeatable behavior that isn't covered by the built-in set. It can even learn to produce music.

GitOps Deployment

FluxCD

apiVersion: source.toolkit.fluxcd.io/v1
kind: HelmRepository
metadata:
  name: nclaw
  namespace: flux-system
spec:
  type: oci
  interval: 10m
  url: oci://ghcr.io/nickalie/charts
---
apiVersion: helm.toolkit.fluxcd.io/v2
kind: HelmRelease
metadata:
  name: nclaw
  namespace: nclaw
spec:
  interval: 10m
  chart:
    spec:
      chart: nclaw
      sourceRef:
        kind: HelmRepository
        name: nclaw
        namespace: flux-system
  values:
    env:
      whitelistChatIds: "123456789"
      webhookBaseDomain: "example.com"
    existingSecret: nclaw-secrets
    claudeCredentialsSecret: claude-credentials
    persistence:
      size: 5Gi

ArgoCD

apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: nclaw
  namespace: argocd
spec:
  project: default
  source:
    chart: nclaw
    repoURL: ghcr.io/nickalie/charts
    targetRevision: "*"
    helm:
      valuesObject:
        env:
          whitelistChatIds: "123456789"
          webhookBaseDomain: "example.com"
        existingSecret: nclaw-secrets
        claudeCredentialsSecret: claude-credentials
        persistence:
          size: 5Gi
  destination:
    server: https://kubernetes.default.svc
    namespace: nclaw
  syncPolicy:
    automated:
      prune: true
      selfHeal: true
    syncOptions:
      - CreateNamespace=true

Development

make run     # Run locally
make lint    # Lint with golangci-lint
make test    # Run tests (requires CGO)
make docker  # Build and run in Docker

License

MIT

Name		Name	Last commit message	Last commit date
Latest commit History 69 Commits
.agents/skills		.agents/skills
.claude/skills		.claude/skills
.github/workflows		.github/workflows
assets		assets
chart		chart
cmd/nclaw		cmd/nclaw
docker		docker
docs/plans		docs/plans
internal		internal
test/install		test/install
.dockerignore		.dockerignore
.gitignore		.gitignore
.golangci.yml		.golangci.yml
.goreleaser.yml		.goreleaser.yml
CLAUDE.md		CLAUDE.md
Makefile		Makefile
README.md		README.md
go.mod		go.mod
go.sum		go.sum
skills-lock.json		skills-lock.json

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nclaw

Table of Contents

Why NClaw

How It Works

Features

Quickstart

Step 1: Create a Telegram Bot

Step 2: Find Your Chat ID

Step 3: Run NClaw

Docker

Claude (default)

Multi-Model

Codex

Copilot

Gemini

All-in-one

Webhooks

Multi-Model

Supported Providers

Model Selection

Local Models

Kubernetes (Helm)

Helm values

Running without Docker

Installation

Homebrew (macOS/Linux)

Scoop (Windows)

Chocolatey (Windows)

Winget (Windows)

AUR (Arch Linux)

DEB / RPM / APK

Binary download

Go install

Usage

Configuration

Environment variables

Config file

Scheduling

Webhooks

Skills

GitOps Deployment

FluxCD

ArgoCD

Development

License

About

Resources

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Stars

Watchers

Forks

Releases

Packages 0

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Contributors

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Languages

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