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Fern

website·Indexed 39 days ago

https://www.buildwithfern.com/

Fern is a developer-first platform that generates interactive API documentation, idiomatic SDKs in 9 languages, and branded CLIs from a single OpenAPI specification. It ensures all surfaces, including Model Context Protocol (MCP) servers and llms.txt files, remain in sync with the API spec to support both human developers and AI agents.

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What's inside Fern

  1. Overview of Fern's Swift SDK generator

    Fern's Swift SDK generator creates idiomatic, production-ready client libraries for iOS, macOS, watchOS, and tvOS. Unlike some generators that produce monolithic files and deep namespaces, Fern generates small, maintainable files with minimal namespacing and resolved symbol collisions.

    Key technical features include:

    • Zero external dependencies.
    • Full support for modern async/await concurrency.
    • Strong typing without force unwrapping or unsafe operations.
    • Forward-compatible structs to prevent breaking changes when new fields are added to API types.
    • Automatic retries with exponential backoff.

  2. Overview of Stainless for SDK Generation

    Stainless is an SDK generation tool that creates client libraries from OpenAPI specifications. It uses a web-based dashboard (Studio) where teams upload specs and use AI-driven suggestions for method names and parameter structures. While primarily focused on SDKs, it offers an early-access documentation platform that generates API and SDK reference documentation from OpenAPI specs and SDK metadata.

  3. Overview of Fern SDK Generation capabilities

    Fern is an SDK generation platform that produces idiomatic SDKs across multiple languages and protocols from a single source of truth. Unlike OpenAPI-only tools, Fern supports REST (OpenAPI), WebSockets (AsyncAPI), OpenRPC, gRPC, and its own native Fern Definition. It synchronizes reference documentation, code samples, and SDKs to prevent drift.

  4. Overview of API testing types and Fern's role

    Effective API testing requires multiple strategies to ensure stability, security, and backward compatibility. Fern provides built-in support to accelerate these testing types:

    • Functional Testing: Validates that endpoints return correct data and status codes. Fern uses Pydantic and Zod for runtime validation to catch type mismatches at compile time.
    • Integration Testing: Verifies data flow across services. Fern's generated SDKs mirror production code, ensuring tests represent real system behavior.
    • Performance Testing: Tests response times and throughput. Fern SDKs include built-in timeout and exponential backoff logic to validate resilience.
    • Security Testing: Validates authentication and authorization. Fern supports Bearer, Basic, API Keys, and OAuth 2.0 with automatic token refresh.
    • Contract Testing: Ensures the API spec matches the implementation and prevents breaking changes. Fern provides fern diff in CI to detect breaking changes before deployment.

  5. Overview of Fern API Toolkit

    Fern is a comprehensive toolkit for the API lifecycle that generates idiomatic SDKs and customizable documentation from API definitions. It supports multiple input formats, including OpenAPI, AsyncAPI, OpenRPC, gRPC, and the Fern Definition. By treating documentation and SDKs as outputs of a single build process, Fern ensures that API reference docs and code snippets remain synchronized with the API spec and the generated libraries, eliminating manual drift.

  6. Overview of GitBook for API Documentation

    GitBook is a web-based documentation platform using a block-based editor (similar to Notion) for technical docs, knowledge bases, and API references. It supports Git synchronization with GitHub and GitLab, allowing documentation to sync between a web editor and code repositories. For APIs, it imports OpenAPI specifications to render interactive reference pages with built-in endpoint testing (powered by Scalar).

  7. Overview of Git-based API documentation (Docs-as-Code)

    Git-based API documentation, or the 'docs-as-code' philosophy, treats documentation files as source code. Content is stored in Markdown files within version control systems (like GitHub or GitLab) alongside the API definition and implementation code. This approach ensures a single source of truth where documentation changes are tracked via commits, reviewed through pull requests, and deployed via automated CI/CD pipelines, significantly reducing 'documentation drift' where docs fall out of sync with the actual API implementation.

  8. Overview of Stainless for SDK generation

    Stainless is a dashboard-driven service for generating client libraries. It connects to GitHub repositories to monitor OpenAPI files and automatically trigger updates to downstream packages. It supports SDK generation for TypeScript, Python, Go, Java, Ruby, and Kotlin, and automates versioning and publishing to package registries.

    Limitations:

    • No support for real-time protocols (WebSockets or Server-Sent Events).
    • No full support for OpenAPI 3.1.1.
    • Documentation product is in beta.
    • No on-premises deployment option.

  9. Overview of GitBook for API Documentation

    GitBook is a cloud-based documentation platform featuring a WYSIWYG editor for collaborative knowledge bases and product guides. It can import OpenAPI specifications to generate reference pages and includes a native interactive API testing playground. It does not generate SDKs or provide automated multi-language code examples.

  10. Overview of SDK publishing platform categories

    Automated package publishing platforms for SDKs generally fall into two categories based on how they determine the next version release:

    1. Spec-driven platforms (e.g., Fern, Speakeasy, APIMatic): Derive versions and releases directly from the API definition. These platforms can fan out a single API change across multiple languages and registries simultaneously.
    2. Commit-driven tools (e.g., semantic-release, release-please, Changesets): Derive versions from commit history (conventional commits) or human-authored changeset files. These typically operate on a per-repository basis.

  11. Overview of Ask Fern conversational AI search

    Ask Fern is an AI-powered search feature that provides a conversational interface (side panel) for API documentation. It uses Retrieval Augmented Generation (RAG) to index documentation pages, SDK code, internal FAQs, help desk tickets, knowledge base articles, and marketing sites. It breaks content into semantic chunks to provide precise answers with direct citations to the source material.

  12. Overview of Fern Agent capabilities

    Fern Agent is a documentation AI agent that identifies problems in documentation by analyzing analytics, search data, and user feedback. It can automatically edit documentation pages and deliver those changes as drafts, branches, or Pull Requests. It is accessible via three primary interfaces: a web Dashboard (as a persistent side panel), Slack (for team-based PR triggers), and the Model Context Protocol (MCP) for integration into developer terminals and coding agents (e.g., Claude Code).