Self-host standalone servers

Deploy standalone Agent Servers using Docker, Docker Compose, or Kubernetes without the LangSmith control plane.

This guide shows you how to deploy standalone Agent Servers directly, without a control plane. You can deploy the server independently and still send traces to LangSmith (self-hosted or SaaS) for observability and evaluation. Standalone servers are production-ready and provide the most lightweight option for running agents.

Overview

You manage a simplified data plane made up of Agent Servers and their required backing services (PostgreSQL, Redis, etc.):

Component	Responsibilities	Where it runs	Who manages it
Control plane	n/a	n/a	n/a
Data plane	Agent Servers Postgres, Redis, etc.	Your infrastructure	You

This option gives you full control over scaling, deployment, and CI/CD pipelines, while still allowing optional integration with LangSmith for tracing and evaluation.

Do not run standalone servers in serverless environments. Scale-to-zero may cause task loss and scaling up will not work reliably.

Workflow

1. Define and test your graph locally using the langgraph-cli or Studio.
2. Package your agent as a Docker image.
3. Deploy the Agent Server to your compute platform of choice (Kubernetes, Docker, VM).
4. Optionally, configure LangSmith API keys and endpoints so the server reports traces and evaluations back to LangSmith (self-hosted or SaaS).

Supported compute platforms

• Kubernetes: Use the LangSmith Helm chart to run Agent Servers in a Kubernetes cluster. This is the recommended option for production-grade deployments.
• Docker: Run in any Docker-supported compute platform (local dev machine, VM, ECS, etc.). This is best suited for development or small-scale workloads.

Prerequisites

1. Use the LangGraph CLI to test your application locally.

2. Use the LangGraph CLI to build a Docker image (i.e. langgraph build).

3. The following environment variables are needed for a data plane deployment.

4. REDIS_URI: Connection details to a Redis instance. Redis will be used as a pub-sub broker to enable streaming real time output from background runs. The value of REDIS_URI must be a valid Redis connection URI.

   Shared Redis Instance Multiple self-hosted deployments can share the same Redis instance. For example, for Deployment A, REDIS_URI can be set to redis://<hostname_1>:<port>/1 and for Deployment B, REDIS_URI can be set to redis://<hostname_1>:<port>/2.

   1 and 2 are different database numbers within the same instance, but <hostname_1> is shared. The same database number cannot be used for separate deployments.

5. DATABASE_URI: Postgres connection details. Postgres will be used to store assistants, threads, runs, persist thread state and long term memory, and to manage the state of the background task queue with ‘exactly once’ semantics. The value of DATABASE_URI must be a valid Postgres connection URI.

   Shared Postgres Instance Multiple self-hosted deployments can share the same Postgres instance. For example, for Deployment A, DATABASE_URI can be set to postgres://<user>:<password>@/<database_name_1>?host=<hostname_1> and for Deployment B, DATABASE_URI can be set to postgres://<user>:<password>@/<database_name_2>?host=<hostname_1>.

   <database_name_1> and database_name_2 are different databases within the same instance, but <hostname_1> is shared. The same database cannot be used for separate deployments.

   You can optionally store checkpoint data in MongoDB instead of PostgreSQL. PostgreSQL is still required for all other server data. See Configure checkpointer backend for details.

6. LANGSMITH_API_KEY: LangSmith API key.

7. LANGGRAPH_CLOUD_LICENSE_KEY: LangSmith license key. This will be used to authenticate ONCE at server start up.

8. LANGSMITH_ENDPOINT: To send traces to a self-hosted LangSmith instance, set LANGSMITH_ENDPOINT to the hostname of the self-hosted LangSmith instance.

9. Egress to https://beacon.langchain.com from your network. This is required for license verification and usage reporting if not running in air-gapped mode. See the Egress documentation for more details.

Kubernetes

Use this Helm chart to deploy an Agent Server to a Kubernetes cluster. This is the recommended setup for production standalone server deployments.

The Helm chart (v0.2.6+) supports MongoDB checkpointing with a bundled instance (dev/testing) or an external deployment (production). Set mongo.enabled: true in your values file. See Configure checkpointer backend for full configuration details.

Docker

This docker example is intended for local development and testing.

Run the following docker command:

docker run \
    --env-file .env \
    -p 8123:8000 \
    -e REDIS_URI="foo" \
    -e DATABASE_URI="bar" \
    -e LANGSMITH_API_KEY="baz" \
    my-image

• You need to replace my-image with the name of the image you built in the prerequisite steps (from langgraph build)

and you should provide appropriate values for REDIS_URI, DATABASE_URI, and LANGSMITH_API_KEY.

• If your application requires additional environment variables, you can pass them in a similar way.

Docker Compose

This Docker Compose example is intended for local development and testing.

Use the following Docker Compose file:

volumes:
    langgraph-data:
        driver: local
services:
    langgraph-redis:
        image: redis:6
        healthcheck:
            test: redis-cli ping
            interval: 5s
            timeout: 1s
            retries: 5
    langgraph-postgres:
        image: postgres:16
        ports:
            - "5432:5432"
        environment:
            POSTGRES_DB: postgres
            POSTGRES_USER: postgres
            POSTGRES_PASSWORD: postgres
        volumes:
            - langgraph-data:/var/lib/postgresql/data
        healthcheck:
            test: pg_isready -U postgres
            start_period: 10s
            timeout: 1s
            retries: 5
            interval: 5s
    langgraph-api:
        image: ${IMAGE_NAME}
        ports:
            - "8123:8000"
        depends_on:
            langgraph-redis:
                condition: service_healthy
            langgraph-postgres:
                condition: service_healthy
        env_file:
            - .env
        environment:
            REDIS_URI: redis://langgraph-redis:6379
            LANGSMITH_API_KEY: ${LANGSMITH_API_KEY}
            DATABASE_URI: postgres://postgres:postgres@langgraph-postgres:5432/postgres?sslmode=disable

Run docker compose up with this file in the same folder.

With MongoDB checkpointing

To store checkpoints in MongoDB instead of PostgreSQL, add a MongoDB service and configure the checkpointer backend. Set the backend to "mongo" in your langgraph.json or use the LS_DEFAULT_CHECKPOINTER_BACKEND environment variable. PostgreSQL is still required for all other server data.

volumes:
    langgraph-data:
        driver: local
    langgraph-mongo-data:
        driver: local
services:
    langgraph-redis:
        image: redis:6
        healthcheck:
            test: redis-cli ping
            interval: 5s
            timeout: 1s
            retries: 5
    langgraph-postgres:
        image: postgres:16
        ports:
            - "5432:5432"
        environment:
            POSTGRES_DB: postgres
            POSTGRES_USER: postgres
            POSTGRES_PASSWORD: postgres
        volumes:
            - langgraph-data:/var/lib/postgresql/data
        healthcheck:
            test: pg_isready -U postgres
            start_period: 10s
            timeout: 1s
            retries: 5
            interval: 5s
    langgraph-mongo:
        image: mongo:7
        command: ["mongod", "--replSet", "rs0"]
        ports:
            - "27017:27017"
        volumes:
            - langgraph-mongo-data:/data/db
        healthcheck:
            test: mongosh --eval "try { rs.status().ok } catch(e) { rs.initiate({_id:'rs0',members:[{_id:0,host:'langgraph-mongo:27017'}]}).ok }" --quiet
            interval: 5s
            timeout: 10s
            retries: 10
            start_period: 10s
    langgraph-api:
        image: ${IMAGE_NAME}
        ports:
            - "8123:8000"
        depends_on:
            langgraph-redis:
                condition: service_healthy
            langgraph-postgres:
                condition: service_healthy
            langgraph-mongo:
                condition: service_healthy
        env_file:
            - .env
        environment:
            REDIS_URI: redis://langgraph-redis:6379
            LANGSMITH_API_KEY: ${LANGSMITH_API_KEY}
            DATABASE_URI: postgres://postgres:postgres@langgraph-postgres:5432/postgres?sslmode=disable
            LS_DEFAULT_CHECKPOINTER_BACKEND: mongo
            LS_MONGODB_URI: mongodb://langgraph-mongo:27017/langgraph?replicaSet=rs0

See Configure checkpointer backend for more details on MongoDB configuration options.

This will launch an Agent Server on port 8123 (change the port mapping in langgraph-api if needed). Test if the application is healthy:

curl --request GET --url 0.0.0.0:8123/ok

Assuming everything is running correctly, you should see a response like:

{"ok":true}

---

Connect these docs to Claude, VSCode, and more via MCP for real-time answers.

Edit this page on GitHub or file an issue.