cortex-docs/cortex

Cortex - Generates interactive API documentation, typed SDKs, and MCP servers from OpenAPI, AsyncAPI, GraphQL, gRPC, OpenRPC, and Markdown.

View on GitHub ↗Jump to charts ↓Open shareable report →

cortex-docs/cortex has 3k+ stars and 150+ forks on GitHub, is written in TypeScript, and was last pushed on Oct 6, 2026. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 1 hour ago
Added to GitGenius on September 22nd, 2026
Created on February 9th, 2015
Open Issues & Pull Requests: 0 (+0)
GitHub issues: Enabled
Number of forks: 177
Total Stargazers: 3,260 (-1)
Total Subscribers: 2 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 2718.0 days
Mean response time: 2592.3 days
90th percentile: 3055.0 days
Tracked items: 15

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Open issues: 0
New in 7 days: 0
Closed in 7 days: 0
Avg open age: N/A days
Stale 30+ days: 0
Stale 90+ days: 0

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • Nice to have (2)
  • Required (1)

Most active issues this week

Sign in to see which issues are moving.
Sign in

Detailed Description

Cortex is a code generation tool that transforms API specifications and Markdown into typed SDKs, interactive documentation, and MCP servers from a single project configuration.

The tool solves the problem of maintaining consistency across API documentation, client libraries, and agent tooling by accepting multiple API specification formats—OpenAPI, AsyncAPI, GraphQL, gRPC, and OpenRPC—alongside custom Markdown, then generating all outputs from these unified sources. It validates each source and displays a generation plan before producing the artifacts, allowing developers to preview what will be created.

Teams should adopt Cortex when they need to generate documentation and SDKs from existing API specifications without manually keeping them synchronized. It suits projects that serve both human developers and AI agents, since it produces interactive documentation for humans alongside an MCP server that exposes typed tools and project context to language models. The tool is particularly valuable for organizations managing multiple API specification formats, as it consolidates them into a single generation workflow rather than requiring separate tools for each format.

The project maintains active continuous integration with automated testing. Development activity shows consistent engagement with the codebase through regular updates and refinements to the generation pipeline.