railway-database▌
davila7/claude-code-templates · updated Apr 8, 2026
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Add official Railway database services. These are maintained templates with pre-configured volumes, networking, and connection variables.
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*orpostgres:*→ Postgresghcr.io/railway/redis*orredis:*→ Redisghcr.io/railway/mysql*ormysql:*→ MySQLghcr.io/railway/mongo*ormongo:*→ MongoDB
Available Databases
| Database | Template Code |
|---|---|
| PostgreSQL | postgres |
| Redis | redis |
| MySQL | mysql |
| MongoDB | mongodb |
Prerequisites
Get project context:
railway status --json
Extract:
id- project IDenvironments.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"
- Check existing DBs via env config query
- If postgres exists: Skip to step 5
- If not exists: Deploy postgres template (fetch template → deploy)
- Wait for deployment to complete
- Identify target service (ask if multiple, or use linked service)
- Use
railway-environmentskill to stage:DATABASE_URL: { "value": "${{Postgres.DATABASE_URL}}" } - Apply changes
"add postgres"
- Check existing DBs via env config query
- If exists: "Postgres already exists in this project"
- If not exists: Deploy postgres template
- Inform user: "Postgres created. Connect a service with:
DATABASE_URL=${{Postgres.DATABASE_URL}}"
"connect the server to redis"
- Check existing DBs via env config query
- If redis exists: Wire up REDIS_URL via environment skill → apply
- If no redis: Ask "No Redis found. Create one?"
- Deploy redis template
- Wire REDIS_URL → apply
Composability
- Connect services: Use
railway-environmentskill to add variable references - View database service: Use
railway-serviceskill - Check logs: Use
railway-deploymentskill
How to use railway-database on Cursor
AI-first code editor with Composer
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
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches railway-database from GitHub repository davila7/claude-code-templates and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
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
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.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 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▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★55 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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