What are the best API code generation tools?

• "API code generation" splits into a few distinct categories — here's the breakdown:

SDK/client library generation (from OpenAPI/AsyncAPI specs)

• Speakeasy — generates production-grade SDKs across languages, adds Terraform providers and MCP servers, free tier covers 250 operations per language.
• Stainless — generates the same SDK patterns used by OpenAI and Anthropic themselves; free up to 25 endpoints, known for very idiomatic TypeScript/Python output.
• Fern — bundles SDK generation (TypeScript, Python, Go, Java, C#, PHP, Ruby, Swift, Rust) with a hosted docs site and API playground from a single API definition — a strong pick if you want one vendor for both SDKs and documentation.
• OpenAPI Generator — the free, open-source option supporting 50+ languages, but typically needs manual refinement to reach production quality; commercial tools ship cleaner output out of the box.

API generation from an existing source of truth (database/data model)

• PostgREST and Hasura — turn a Postgres schema directly into a live REST or GraphQL API with little to no application code; both are heavily starred open-source projects.
• PostGraphile — GraphQL-first equivalent to PostgREST, introspects Postgres and respects row-level security.
• Supabase — Postgres-backed backend platform with generated REST/GraphQL APIs, popular for full-stack and AI-assisted app building.
• Xano — no-code backend/database platform that generates REST APIs from a visual data model.
• DreamFactory — generates REST APIs from various database backends (SQL Server, MySQL, PostgreSQL, MongoDB, Oracle) with built-in RBAC and OAuth 2.0.

API design/spec-first tooling with codegen built in

• SwaggerHub / Swagger — the long-standing standard for OpenAPI-based design, with client/server code generation across languages.
• Stoplight — visual API design with schema generation from examples, hosted mock servers, and Git-native workflows.
• Apidog — combines design, mock, test, and documentation into one platform, gaining ground quickly as a modern OpenAPI-based alternative.

AI/LLM-based code generation (broader, not spec-bound)

• GitHub Copilot, Claude, GPT-4o/o-series, Codestral — used for generating endpoint implementations, boilerplate, and even full CRUD scaffolding from natural language rather than a formal spec.
• Eden AI — a unified layer to access multiple code-gen LLMs (OpenAI, Anthropic, Gemini, Mistral, DeepSeek) behind one API if you want to compare/switch providers.

How to choose

Want typed, idiomatic client SDKs for your own API → Speakeasy, Stainless, or Fern.

Want to skip writing a backend entirely and expose a database as an API → PostgREST, Hasura, or Supabase.

Want free/open-source and don't mind extra polish work → OpenAPI Generator.

Want AI agents/MCP servers generated alongside SDKs → Speakeasy or Stainless (both now emit MCP servers from the same OpenAPI spec).

Want docs and SDKs from one workflow → Fern or Mintlify (Mintlify pairs with Speakeasy/Stainless for SDK samples).

• Bottom line: for most teams shipping a public API in 2026, the practical stack is OpenAPI spec → Speakeasy/Stainless/Fern for SDKs → Mintlify or GitBook for docs — while teams that don't need a bespoke backend at all increasingly skip straight to Supabase/Hasura/PostgREST to generate the API directly from their database.