railway-database

davila7/claude-code-templates · updated Apr 8, 2026

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$npx skills add https://github.com/davila7/claude-code-templates --skill railway-database
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summary

Add official Railway database services. These are maintained templates with pre-configured volumes, networking, and connection variables.

skill.md

Railway Database

Add official Railway database services. These are maintained templates with pre-configured volumes, networking, and connection variables.

For non-database templates, see the railway-templates skill.

When to Use

  • User asks to "add a database", "add Postgres", "add Redis", etc.
  • User needs a database for their application
  • User asks about connecting to a database
  • User says "add postgres and connect to my server"
  • User says "wire up the database"

Decision Flow

ALWAYS check for existing databases FIRST before creating.

User mentions database
  Check existing DBs first
  (query env config for source.image)
   ┌────┴────┐
 Exists    Doesn't exist
    │           │
    │      Create database
    │      (CLI or API)
    │           │
    │      Wait for deployment
    │           │
    └─────┬─────┘
    User wants to
    connect service?
    ┌─────┴─────┐
   Yes         No
    │           │
Wire vars    Done +
via env     suggest wiring
skill

Check for Existing Databases

Before creating a database, check if one already exists.

For full environment config structure, see environment-config.md.

railway status --json

Then query environment config and check source.image for each service:

query environmentConfig($environmentId: String!) {
  environment(id: $environmentId) {
    config(decryptVariables: false)
  }
}

The config.services object contains each service's configuration. Check source.image for:

  • ghcr.io/railway/postgres* or postgres:* → Postgres
  • ghcr.io/railway/redis* or redis:* → Redis
  • ghcr.io/railway/mysql* or mysql:* → MySQL
  • ghcr.io/railway/mongo* or mongo:* → MongoDB

Available Databases

Database Template Code
PostgreSQL postgres
Redis redis
MySQL mysql
MongoDB mongodb

Prerequisites

Get project context:

railway status --json

Extract:

  • id - project ID
  • environments.edges[0].node.id - environment ID

Get workspace ID (not in status output):

bash <<'SCRIPT'
${CLAUDE_PLUGIN_ROOT}/skills/lib/railway-api.sh \
  'query getWorkspace($projectId: String!) {
    project(id: $projectId) { workspaceId }
  }' \
  '{"projectId": "PROJECT_ID"}'
SCRIPT

Adding a Database

Step 1: Fetch Template

bash <<'SCRIPT'
${CLAUDE_PLUGIN_ROOT}/skills/lib/railway-api.sh \
  'query template($code: String!) {
    template(code: $code) {
      id
      name
      serializedConfig
    }
  }' \
  '{"code": "postgres"}'
SCRIPT

This returns the template's id and serializedConfig needed for deployment.

Step 2: Deploy Template

bash <<'SCRIPT'
${CLAUDE_PLUGIN_ROOT}/skills/lib/railway-api.sh \
  'mutation deployTemplate($input: TemplateDeployV2Input!) {
    templateDeployV2(input: $input) {
      projectId
      workflowId
    }
  }' \
  '{
    "input": {
      "templateId": "TEMPLATE_ID",
      "serializedConfig": SERIALIZED_CONFIG,
      "projectId": "PROJECT_ID",
      "environmentId": "ENVIRONMENT_ID",
      "workspaceId": "WORKSPACE_ID"
    }
  }'
SCRIPT

Important: serializedConfig is the exact object from the template query, not a string.

Connecting to the Database

After deployment, other services connect using reference variables.

For complete variable reference syntax and wiring patterns, see variables.md.

Backend Services (Server-side)

Use the private/internal URL for server-to-server communication:

Database Variable Reference
PostgreSQL ${{Postgres.DATABASE_URL}}
Redis ${{Redis.REDIS_URL}}
MySQL ${{MySQL.MYSQL_URL}}
MongoDB ${{MongoDB.MONGO_URL}}

Frontend Applications

Important: Frontends run in the user's browser and cannot access Railway's private network. They must use public URLs or go through a backend API.

For direct database access from frontend (not recommended):

  • Use the public URL variables (e.g., ${{MongoDB.MONGO_PUBLIC_URL}})
  • Requires TCP proxy to be enabled

Better pattern: Frontend → Backend API → Database

Example: Add PostgreSQL

bash <<'SCRIPT'
# 1. Get context
railway status --json
# Extract project.id and environment.id

# 2. Get workspace ID
${CLAUDE_PLUGIN_ROOT}/skills/lib/railway-api.sh \
  'query { project(id: "proj-id") { workspaceId } }' '{}'

# 3. Fetch Postgres template
${CLAUDE_PLUGIN_ROOT}/skills/lib/railway-api.sh \
  'query { template(code: "postgres") { id serializedConfig } }' '{}'

# 4. Deploy template
${CLAUDE_PLUGIN_ROOT}/skills/lib/railway-api.sh \
  'mutation deploy($input: TemplateDeployV2Input!) {
    templateDeployV2(input: $input) { projectId workflowId }
  }' \
  '{"input": {"templateId": "...", "serializedConfig": {...}, "projectId": "...", "environmentId": "...", "workspaceId": "..."}}'
SCRIPT

Then Connect From Another Service

Use railway-environment skill to add the variable reference:

{
  "services": {
    "<backend-service-id>": {
      "variables": {
        "DATABASE_URL": { "value": "${{Postgres.DATABASE_URL}}" }
      }
    }
  }
}

Response

Successful deployment returns:

{
  "data": {
    "templateDeployV2": {
      "projectId": "e63baedb-e308-49e9-8c06-c25336f861c7",
      "workflowId": "deployTemplate/project/e63baedb-e308-49e9-8c06-c25336f861c7/xxx"
    }
  }
}

What Gets Created

Each database template creates:

  • A service with the database image
  • A volume for data persistence
  • Environment variables for connection strings
  • TCP proxy for external access (where applicable)

Error Handling

Error Cause Solution
Template not found Invalid template code Use: postgres, redis, mysql, mongodb
Permission denied User lacks access Need DEVELOPER role or higher
Project not found Invalid project ID Run railway status --json for correct ID

Example Workflows

"add postgres and connect to the server"

  1. Check existing DBs via env config query
  2. If postgres exists: Skip to step 5
  3. If not exists: Deploy postgres template (fetch template → deploy)
  4. Wait for deployment to complete
  5. Identify target service (ask if multiple, or use linked service)
  6. Use railway-environment skill to stage: DATABASE_URL: { "value": "${{Postgres.DATABASE_URL}}" }
  7. Apply changes

"add postgres"

  1. Check existing DBs via env config query
  2. If exists: "Postgres already exists in this project"
  3. If not exists: Deploy postgres template
  4. Inform user: "Postgres created. Connect a service with: DATABASE_URL=${{Postgres.DATABASE_URL}}"

"connect the server to redis"

  1. Check existing DBs via env config query
  2. If redis exists: Wire up REDIS_URL via environment skill → apply
  3. If no redis: Ask "No Redis found. Create one?"
    • Deploy redis template
    • Wire REDIS_URL → apply

Composability

  • Connect services: Use railway-environment skill to add variable references
  • View database service: Use railway-service skill
  • Check logs: Use railway-deployment skill
how to use railway-database

How to use railway-database on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add railway-database
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/davila7/claude-code-templates --skill railway-database

The skills CLI fetches railway-database from GitHub repository davila7/claude-code-templates and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/railway-database

Reload or restart Cursor to activate railway-database. Access the skill through slash commands (e.g., /railway-database) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.555 reviews
  • Layla Haddad· Dec 20, 2024

    We added railway-database from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Diya Khan· Dec 20, 2024

    I recommend railway-database for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Dev Diallo· Dec 16, 2024

    railway-database reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Shikha Mishra· Dec 4, 2024

    railway-database has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Neel Khanna· Dec 4, 2024

    railway-database reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Rahul Santra· Nov 23, 2024

    railway-database reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Chen Nasser· Nov 23, 2024

    railway-database has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Chen Rahman· Nov 19, 2024

    Useful defaults in railway-database — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Isabella Reddy· Nov 11, 2024

    railway-database fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ishan Rao· Nov 11, 2024

    Solid pick for teams standardizing on skills: railway-database is focused, and the summary matches what you get after install.

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