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AI-Powered Development

Encore’s open-source SDK lets agents define the infrastructure each feature needs directly in application code. Encore runs the app with working databases, queues, buckets, and more, so you can test and validate the complete feature immediately.

Start buildingTalk to an engineer→
~/orders — claude
Claude Code
Claude Code v2.1.180Opus 4.8 · Encore MCP connected~/orders
Infra from codereading the code…
SQLDatabaseorders · postgres
Topicorders · pub/sub
Bucketdeclared in code
not running yet

Guardrails that make AI reliable

Encore's structured APIs and infrastructure primitives give AI tools a reliable framework. With Encore-specific rules and MCP integration, AI understands your patterns, can provision infrastructure with guardrails, and generates code that actually works.

  • ✓Infrastructure provisioning with guardrails
  • ✓Type-safe code generation
  • ✓Context-aware suggestions
  • ✓Architecture introspection via MCP
1
Agent writes codetypes + infra declarations
2
Runs against real infradatabases, queues, buckets
3
Reads the failuretraces, logs, type errors
4
Corrects itselfbefore a human reviews

The loop closes before the pull request exists.

Infrastructure with guardrails

AI can provision databases, pub/sub topics, and other infrastructure in AWS/GCP using Encore's primitives. Guardrails ensure it follows best practices automatically.

Context-aware code generation

Encore-specific rules help AI understand your patterns. Generated code follows your existing service structure, API conventions, and infrastructure setup.

Instant verification

Run encore run to immediately test AI-generated code with real infrastructure, not mocks.

Works with any agent or AI coding tool

Use Encore with Cursor, Claude Code, GitHub Copilot, VS Code, Zed, and more. Generate the right configuration with encore llm-rules init, or install Encore’s agent skills with npx add-skill encoredev/skills.

Agents get Encore-specific coding rules, skills for building and migrating apps, and local MCP access to your architecture, APIs, database schemas, and traces.

MCP server documentation→
CursorClaude Code
GitHub Copilot
Antigravity

Why AI works better with Encore

Traditional codebases are opaque to AI: configuration scattered across YAML, infrastructure defined separately, service relationships unclear. Encore applications are self-describing, so an assistant can read the architecture instead of guessing at it.

Without Encore
  • AI guesses at infrastructure setup
  • Generated code requires manual wiring
  • No visibility into existing patterns
  • Testing requires manual mock setup
With Encore
  • AI understands architecture via MCP and Encore rules
  • Generated code follows your patterns automatically
  • Infrastructure provisioned with guardrails in AWS/GCP
  • Type-safe code that passes validation
  • Instant testing with real infrastructure

Ship AI-generated code with confidence

Encore's type system catches errors before they reach production. AI-generated code is validated against your API schemas, database types, and infrastructure definitions.

Combined with preview environments, you can test AI-generated changes in isolation before merging to production.

Validated automatically
Encore's type systemcompile time
Your API schemasrequest + response
Database typesqueries checked
Infrastructure definitionsdeclared in code
“What used to take days or weeks of back-and-forth between developers and infra teams is now automated and completed in minutes.”
Josef Sima, Engineering Director at Groupon→
2–3xfaster development speed
90%shorter time to market
// POWERING DEVELOPMENT AT
GrouponPave BankBookshop.orgCoinbasePalletGradient Labs

Build with AI, ship with confidence

See how Encore enables AI-powered development at scale.

Get started

Install the Encore CLI with `brew install encoredev/tap/encore`, then run `encore app create my-app` and follow the prompts to scaffold a new backend and help me explore how to build with encore.

Copy

Paste into your coding agent to install Encore and scaffold an app.