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/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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langchain-skills
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Install
$ npx -y skills add langchain-ai/langchain-skills --skill langgraph-cli --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/langgraph-cli

Context preview

The summary Claude sees to decide when to auto-load this skill.

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.

SKILL.md

langgraph-cli.SKILL.md
name: langgraph-cli
description: "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."

<overview> The `langgraph` CLI manages the full lifecycle of LangGraph applications — from scaffolding a new project to deploying it to LangGraph Platform (LangSmith Deployments).

Key commands:

  • **`langgraph new`** — Scaffold a project from a template
  • **`langgraph dev`** — Run locally with hot reload (no Docker)
  • **`langgraph build`** — Build a Docker image
  • **`langgraph up`** — Launch locally via Docker Compose
  • **`langgraph deploy`** — Ship to LangGraph Platform
  • **`langgraph 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.json` configuration
  • 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 (debu
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⚠️ — This project is in early development. APIs and skill content may change. Agent skills for building agents with LangChain, LangGraph, and Deep Agents. For LangSmith-specific trace and dataset workflows, use langsmith-skills.

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