
langgraph-cli
INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/langchain-ai/langchain-skills --skill langgraph-cli- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads langgraph-cli automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
Security audits
Independent scans of the skill's instructions and bundled files.
SKILL.md
The instructions your agent reads when the skill is triggered.
Key commands:
langgraph new— Scaffold a project from a templatelanggraph dev— Run locally with hot reload (no Docker)langgraph build— Build a Docker imagelanggraph up— Launch locally via Docker Composelanggraph deploy— Ship to LangGraph Platformlanggraph dockerfile— Generate a Dockerfile
All commands (except new) read from a langgraph.json config file in the project root.
</overview>
When to use
Use this skill when the user wants to:
- Scaffold a new LangGraph project
- Run a local development or production-like server
- Build or deploy a LangGraph application
- Understand or edit
langgraph.jsonconfiguration - Manage LangSmith Deployments (list, delete, view logs)
Installation
# Python
pip install 'langgraph-cli[inmem]' # includes langgraph dev support
pip install langgraph-cli # without dev server (build/up/deploy only)
# if using UV as package manager
uv add "langgraph-cli[inmem]" # includes langgraph dev support
uv add langgraph-cli # without dev server (build/up/deploy only)
# JavaScript
npx @langchain/langgraph-cli # use on demand
npm install -g @langchain/langgraph-cli # install globally (available as langgraphjs)
Commands
langgraph new [PATH]
Scaffold a new project from a template.
langgraph new # interactive template selection
langgraph new ./my-agent # create in specific directory
langgraph new --template agent-python # skip prompt, use template directly
Available templates: deep-agent-python, deep-agent-js, agent-python, new-langgraph-project-python, new-langgraph-project-js
langgraph dev
Run a local development server with hot reloading. No Docker required.
langgraph dev # default: localhost:2024
langgraph dev --port 8000 # custom port
langgraph dev --config ./langgraph.json # explicit config path
langgraph dev --no-reload # disable hot reload
langgraph dev --no-browser # don't auto-open LangGraph Studio
langgraph dev --host 0.0.0.0 # bind to all interfaces (trusted networks only)
langgraph dev --tunnel # expose via Cloudflare tunnel for remote access
langgraph dev --debug-port 5678 # enable remote debugger (requires debugpy)
langgraph dev --n-jobs-per-worker 20 # max concurrent jobs per worker (default: 10)
langgraph build
Build a Docker image for the LangGraph API server.
langgraph build -t my-image # required: tag the image
langgraph build -t my-image --no-pull # use locally-built base images
langgraph build -t my-image -c langgraph.json # explicit config
langgraph build -t my-image --base-image langchain/langgraph-server:0.2.18 # pin base version
langgraph up
Launch the LangGraph API server via Docker Compose (includes Postgres).
langgraph up # default port 8123
langgraph up --port 8000 # custom port
langgraph up --watch # restart on file changes
langgraph up --recreate # force fresh build (useful for pre-deploy validation)
langgraph up --postgres-uri postgresql://... # external Postgres
langgraph up --no-pull # use local images (after langgraph build)
langgraph up --image my-image # skip build, use pre-built image
langgraph up -d docker-compose.yml # add extra Docker services
langgraph up --debugger-port 8124 # serve debugger UI
langgraph up --wait # block until services are healthy
langgraph deploy
Build and deploy to LangGraph Platform (LangSmith Deployments). Requires Docker. On Apple Silicon (M1/M2/M3), Docker Buildx is also required for cross-compiling to linux/amd64.
langgraph deploy # deploy, name defaults to directory name
langgraph deploy --name my-agent # explicit deployment name
langgraph deploy --deployment-type prod # production deployment (default: dev)
langgraph deploy --tag v1.2.0 # custom image tag (default: latest)
langgraph deploy --deployment-id <id> # update an existing deployment by ID
langgraph deploy --config ./langgraph.json # explicit config path
langgraph deploy --no-wait # don't wait for deployment status
langgraph deploy --verbose # show detailed server logs
Prereq: LANGSMITH_API_KEY in environment or .env.
langgraph deploy also accepts build flags: --base-image, --pull/--no-pull.
langgraph deploy list
langgraph deploy list # list all deployments
langgraph deploy list --name-contains bot # filter by name
langgraph deploy delete
langgraph deploy delete <deployment-id> # interactive confirmation
langgraph deploy delete <deployment-id> --force # skip confirmation
langgraph deploy logs
langgraph deploy logs # runtime logs, last 100
langgraph deploy logs --name my-agent # by deployment name
langgraph deploy logs --deployment-id <id> # by deployment ID
langgraph deploy logs --type build # build logs instead of runtime
langgraph deploy logs -f # follow/stream logs
langgraph deploy logs --level error # filter by level (debug|info|warning|error|critical)
langgraph deploy logs -q "timeout" # search filter
langgraph deploy logs --limit 500 # more entries
langgraph deploy logs --start-time 2026-03-08T00:00:00Z # time range
langgraph dockerfile <SAVE_PATH>
Generate a Dockerfile (and optionally Docker Compose files) without building.
langgraph dockerfile ./Dockerfile # generate Dockerfile
langgraph dockerfile ./Dockerfile --add-docker-compose # also generate compose + .env + .dockerignore
langgraph.json reference
The configuration file used by all CLI commands (dev, build, up, deploy). Defaults to langgraph.json in the current directory.
Minimal config (Python)
{
"dependencies": ["."],
"graphs": {
"agent": "./my_agent/agent.py:graph"
},
"env": "./.env"
}
Minimal config (JavaScript)
{
"dependencies": ["."],
"graphs": {
"agent": "./src/agent.js:graph"
},
"env": "./.env"
}
Full config with all keys
{
"dependencies": [".", "langchain_openai", "./local_package"],
"graphs": {
"agent": "./my_agent/agent.py:graph",
"retriever": "./my_agent/rag.py:rag_graph"
},
"env": "./.env",
"python_version": "3.12",
"pip_config_file": "./pip.conf",
"dockerfile_lines": [
"RUN apt-get update && apt-get install -y ffmpeg"
]
}
Key reference
| Key | Required | Description |
|---|---|---|
dependencies | Yes | Array of dependencies. "." looks for local packages via pyproject.toml, setup.py, requirements.txt, or package.json. Can also be paths to subdirectories ("./my_pkg") or package names ("langchain_openai"). |
graphs | Yes | Mapping of graph ID to path. Format: ./path/to/file.py:variable (Python) or ./path/to/file.js:function (JS). The variable must be a CompiledGraph or a function returning one. Multiple graphs supported. |
env | No | Path to a .env file (string) OR an inline mapping of env var names to values (object). Used by langgraph dev and langgraph up locally. langgraph deploy reads from this file and adds the variables as deployment secrets. |
python_version | No | "3.11", "3.12", or "3.13". Defaults to "3.11". |
node_version | No | Node.js version for JS projects. |
pip_config_file | No | Path to a pip config file for custom package indexes. |
dockerfile_lines | No | Array of additional Dockerfile lines appended after the base image import. Use for system packages, binaries, or custom setup. |
Typical workflow
- Scaffold —
langgraph newto create a project from a template. - Configure — Edit
langgraph.json: set dependencies, pointgraphsat your compiled graph(s), add.env. - Develop —
langgraph devfor rapid local iteration with hot reload (no Docker, port 2024). - Validate —
langgraph up --recreateto test in a production-like Docker stack (port 8123, includes Postgres). - Deploy —
langgraph deployto ship to LangGraph Platform (LangSmith Deployments). - Monitor —
langgraph deploy logs -fto tail runtime logs;--type buildfor build logs.
langgraph dev vs langgraph up
| Feature | langgraph dev | langgraph up |
|---|---|---|
| Docker required | No | Yes |
| Install | pip install 'langgraph-cli[inmem]' | pip install langgraph-cli |
| Primary use | Rapid development & testing | Production-like validation |
| State persistence | In-memory / pickled to local dir | PostgreSQL |
| Hot reloading | Yes (default) | Optional (--watch) |
| Default port | 2024 | 8123 |
| Resource usage | Lightweight | Heavier (Docker containers for server, Postgres, Redis) |
| IDE debugging | Built-in DAP support (--debug-port) | Container debugging |
Gotchas
langgraph deployrequires Docker — On Apple Silicon (M1/M2/M3), Docker Buildx is also required for cross-compiling tolinux/amd64.langgraph deploycan only update its own deployments — Deployments created through the LangSmith UI or GitHub integration cannot be updated withlanggraph deploy. Use the UI for those.dependenciesmust include all packages — Thedependenciesarray inlanggraph.jsonmust point to where your package config lives (e.g.,"."for root). The actual packages are resolved frompyproject.toml,requirements.txt, orpackage.jsonat that location.langgraph devruns without Docker — It runs directly in your environment. If your code depends on system packages (e.g.,ffmpeg), they must be installed locally. Uselanggraph upto validate Docker builds.- JavaScript CLI — Use
npx @langchain/langgraph-cli <command>(orlanggraphjsif installed globally vianpm install -g @langchain/langgraph-cli). - API key —
LANGSMITH_API_KEYis required forlanggraph deploy. Forlanggraph dev, it is optional — the server runs without it, but you won't get traces in LangSmith. Can also be set viaLANGGRAPH_HOST_API_KEYorLANGCHAIN_API_KEY.
FAQ
What does the langgraph-cli skill do?
INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.
How do I install langgraph-cli?
Run npx skills add https://github.com/langchain-ai/langchain-skills --skill langgraph-cli in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/langgraph-cli/ (personal) or .claude/skills/langgraph-cli/ (project).
Which AI agents can use langgraph-cli?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is langgraph-cli safe to install?
Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed. As with any skill, read the SKILL.md and bundled scripts before installing.
Who maintains langgraph-cli?
It is published by langchain-ai in langchain-ai/langchain-skills, and it is an official skill from the maker of the technology it covers. It has 9,045 recorded installs.
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