Octri.dev

Product Introduction

1. Definition: Octri.dev is a comprehensive API lifecycle platform that transforms a single OpenAPI specification into four synchronized products: a customizable documentation site, idiomatic client SDKs in ten programming languages, an MCP (Model Context Protocol) server for AI agents, and integrated production monitoring. It is a technical tool for API-first development and developer experience (DX) automation.
2. Core Value Proposition: Octri exists to eliminate the manual, error-prone, and siloed processes of building API documentation, client libraries, and observability tools. Its primary value is providing a single source of truth (the OpenAPI spec) that automatically generates and maintains a complete, production-ready API ecosystem, ensuring consistency and drastically reducing integration failures and support burden.

Main Features

1. API Studio (Documentation Generator): Generates a fully hosted, customizable documentation website from an OpenAPI, Swagger, Postman, or AsyncAPI spec. It features a three-column layout for endpoint references (parameters, schemas, SDK examples), a live "try it" playground, and supports MDX for custom guide pages. AI drafts initial content, which can be edited in-place without touching the source YAML/JSON. It publishes to a custom domain.
2. SDK Studio (Multi-Language Client Generator): Produces high-quality, idiomatic Software Development Kits (SDKs) in TypeScript, Python, Go, Java, Dart, Ruby, PHP, Rust, Swift, and Kotlin. It allows deep configuration (method renaming, endpoint exclusion, HTTP engine selection, code style) without forking the generator. It features custom hooks and automatically publishes to native package registries (npm, PyPI, Maven Central, crates.io, RubyGems, pub.dev, Packagist).
3. Integrated SDK Monitoring & Observability: A unique feature where telemetry is compiled directly into the generated SDKs. When these SDKs are used in production, errors, latency, and usage data are reported back. This provides structured logs, error grouping, distributed tracing across client and server, service dependency mapping, N+1 query detection, synthetic uptime checks, and alerts. Data is redacted client-side for security.
4. MCP (Model Context Protocol) Server Generator: Automatically creates an MCP server that exposes the API's documentation and endpoints as tools for AI agents like those in Claude or Cursor. This prevents AI hallucination of API details by giving agents direct, real-time access to the actual API spec and the ability to make live calls, curated by the same rules as the SDKs.

Problems Solved

1. Pain Point: The massive fragmentation and manual effort in the API toolchain. Teams typically use separate tools for docs (e.g., Redocly, Stoplight), SDK generation (e.g., OpenAPI Generator), and monitoring (e.g., Sentry, Datadog), leading to inconsistency, drift, and high maintenance overhead.
2. Target Audience: API Product Managers & Developer Advocates needing polished, consistent docs and SDKs; Backend & Platform Engineers tasked with improving developer experience and reducing integration support; DevOps & SREs responsible for API reliability who lack visibility into client-side failures.
3. Use Cases: Launching a new public API quickly with professional-grade docs and SDKs. Scaling an existing API where hand-written SDKs and docs have become unmanageable. Reducing support tickets caused by integration errors by detecting SDK failures before users report them. Enabling AI agent integration safely and accurately without manual tool-building.

Unique Advantages

1. Differentiation: Unlike standalone documentation generators or basic SDK tools, Octri provides a unified, four-product platform with a feedback loop. Competitors stop at generation; Octri adds production monitoring from the generated artifacts themselves. Unlike generic APM tools, its monitoring is semantically aware of the API structure because it originates from the same spec.
2. Key Innovation: The closed-loop observability integrated into generated SDKs. This transforms client libraries from passive, dumb wrappers into active reporting agents. The platform's core innovation is treating the OpenAPI spec as a living blueprint that drives not just static artifacts, but a dynamic runtime feedback system for the entire API ecosystem.

Frequently Asked Questions (FAQ)

1. How does Octri's monitoring work, and is it secure? Monitoring is opt-in and compiles lightweight telemetry directly into your generated SDKs. When an error occurs in a client application using the SDK, it sends a structured event to Octri. Security is multi-layered: credentials and direct identifiers (tokens, emails, IPs) are redacted in the client-side code before the event leaves the user's process, and are redacted again at ingestion. Octri offers a pre-signed GDPR Data Processing Agreement (DPA).
2. Can I customize the generated SDKs and documentation, or am I locked into the default output? Yes, extensive customization is a core feature. For SDKs, you can rename methods, exclude endpoints, choose HTTP clients, and inject custom code via hooks. For documentation, you can fully edit AI-generated text, add custom MDX pages, and control navigation. Regeneration is smart and works around your edits, only updating parts of the docs or SDKs that correspond to changes in the underlying OpenAPI spec.
3. What happens when I update my OpenAPI specification? Changes trigger a rebuild of all four products (docs, SDKs, MCP, monitoring), but nothing is published automatically. You review a draft and a diff. Only after your approval are new SDK versions published to registries and documentation updates deployed. This prevents unexpected breaking changes from reaching users.
4. I'm already using another docs tool (like ReadMe or Swagger UI) or SDK generator. How difficult is migration? Octri provides importers that read configuration from other tools (like a docs.config.yaml) to recreate your structure. Migrating the basic setup for docs and SDKs typically takes less than a day. The complexity depends on the amount of deeply custom, hand-written code or components in your existing setup, which may require reimplementation.
5. Is my OpenAPI spec or telemetry data used to train AI models? No. According to Octri's policy, your specification data and any production monitoring telemetry are not used to train any third-party or internal AI models. Your data is processed solely to provide the platform's services.