---
id: kb-013
title: Fumadocs LLM-Friendly Features Implementation Plan
scope:
  type: project
  id: 4sgm
purpose: analysis-fumadocs-llm
tags:
  - documentation
  - fumadocs
  - llm-friendly
topics:
  - engineering
  - frontend
version: 1
created: 2025-11-22
updated: 2025-11-22
author: droid-agent
status: final
related_ids:
  - kb-011
external_refs: []
---

# Fumadocs LLM-Friendly Features Analysis

## Executive Summary

Fumadocs, being Next.js based, can not only match but exceed the LLM-friendly features of MkDocs. This plan outlines how to implement sitemaps, complete reference dumps, and structured exports specifically for AI assistants.

## Comparison: MkDocs vs. Fumadocs

| Feature | MkDocs | Fumadocs |
|---------|--------|----------|
| `/llms.txt` Sitemap | ✅ Built-in | ✅ Custom Route (Easy) |
| `/llms-full.txt` Dump | ✅ Built-in | ✅ Custom Route (Easy) |
| Markdown Export | ✅ Extension | ✅ Content Negotiation |
| JSON Export | ❌ No | ✅ Custom API Route |
| Search API | ❌ No | ✅ Built-in (Shiki) |
| SSR/Dynamic Content | ❌ No | ✅ Full Support |

---

## Implementation Plan

### Phase 1: Core LLM Features
- **`/llms.txt`**: Create a plain-text sitemap route for discovery.
- **`/llms-full.txt`**: Create a single-file dump of all documentation for context injection.
- **JSON Export**: Implement `/api/docs/export` for structured parsing.

### Phase 2: Markdown & Metadata
- **Markdown Negotiation**: Support `Accept: text/markdown` headers to serve raw MD content.
- **Structured Metadata**: Leverage YAML frontmatter for machine-readable categorization.

### Phase 3: Docstring Integration
- **pdoc + MDX**: Use `pdoc` to generate HTML from Python docstrings and wrap them in MDX components for a seamless UI.

---

## Conclusion

By investing ~1.5 hours in Phase 4 of the documentation migration, Fumadocs will provide a superior experience for both human readers and AI assistants, leveraging the full power of Next.js API routes and React components.
