Deploy Memory

Deploy and Host Memory with Railway

Deploy Memory

Just deployed

Just deployed

/var/lib/postgresql/data

Just deployed

/data

Just deployed

Just deployed

/data

memory-documents

Bucket

Just deployed

Deploy and Host Memory with Railway

Memory is a self-hosted knowledge graph and memory service for AI agents and teams. This template provisions the full stack with Railway.

About Hosting Memory

The template creates five services and a Railway bucket: Postgres with pgvector, xberg for document extraction, Zitadel for authentication, the Memory API/MCP server, and the Memory web UI. After deployment, a short one-time Zitadel bootstrap connects the server and web UI.

Why Deploy Memory

Deploy Memory on Railway to get a managed Postgres database, private service networking, public HTTPS domains, persistent volumes and a reproducible full-stack deployment without running your own Kubernetes cluster.

Common Use Cases

  • Give AI agents persistent memory and a queryable knowledge graph
  • Search and organize documents, notes and research
  • Run a private MCP server for coding agents
  • Host a team knowledge base with authenticated web access

Dependencies for Memory Hosting

Memory needs Postgres with the pgvector extension, an S3-compatible document store, an OIDC provider, and the Memory server and web UI images.

Deployment Dependencies

  • pgvector/pgvector:pg18-trixie
  • ghcr.io/xberg-io/xberg:1.3.0
  • ghcr.io/zitadel/zitadel:v4.17.3
  • ghcr.io/emergent-company/memory-server:0.96.0
  • ghcr.io/emergent-company/memory-web-ui:0.96.0

Configure your AI provider in Memory after deployment. AI credentials are not baked into the template.


Template Content

memory-documents

Bucket

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