Apple Books MCP

MCP server: vgnshiyer/apple-books-mcp

Install: npx -y @anthropic-ai/claude-code mcp add apple-books -- uvx apple-books-mcp

Tools Reference

Critical: Color Extraction Strategy

get_book_annotations does NOT return colors. describe_annotation returns colors but one at a time — 150+ calls for a single book.

Solution: Call get_highlights_by_color once per color (5 total calls), then cross-reference annotation IDs programmatically.

Available colors: PINK, BLUE, YELLOW, GREEN, PURPLE
Underlines: color = null, is_underline = 1

Build the Color Map

import json, glob

# After calling get_highlights_by_color for PINK, BLUE, YELLOW, GREEN, PURPLE
# Results save to files when they exceed token limits

ann_color = {}
colors = ["PINK", "BLUE", "YELLOW", "GREEN", "PURPLE"]

for color_file, color in zip(sorted(glob.glob("path/to/results/*.txt")), colors):
    with open(color_file, 'r') as f:
        data = json.load(f)
    current_id = None
    for line in data.get("text", "").split("\n"):
        line = line.strip()
        if line.startswith("ID: "):
            current_id = line.split("ID: ")[1].strip()
        elif line.startswith("Selected text: ") and current_id:
            selected = line[len("Selected text: "):]
            if selected and selected != "None":
                ann_color[current_id] = color

# Look up: ann_color.get(str(annotation_id), None)  # None = underline

Workflow: Extract Highlights for a Book List

Step 1: Match Books

Call list_all_books and match against user's list. Tips:

• Books may appear under translated titles (e.g., Russian editions)
• PDFs often have garbled or filename-based titles
• Use partial/fuzzy matching — "Vignelli Canon" may appear as just "canon"
• Same book may exist in multiple editions (different IDs)

Step 2: Get Annotations per Book

get_book_annotations(book_id="531")

Returns: ID, selected_text, representative_text, note, chapter, location, modification date. Filter out entries where selected_text is None (empty bookmarks).

Step 3: Get Colors (Batch)

get_highlights_by_color(color="PINK")
get_highlights_by_color(color="BLUE")
get_highlights_by_color(color="YELLOW")
get_highlights_by_color(color="GREEN")
get_highlights_by_color(color="PURPLE")

Results are large (100k-400k chars). Use Python to parse.

Step 4: Export to Markdown

color_emoji = {
    "PINK": "🩷", "BLUE": "🔵", "YELLOW": "🟡",
    "GREEN": "🟢", "PURPLE": "🟣",
}

lines = [f"# {title}", f"**{author}**", "", "---", ""]
for ann_id, text in annotations:
    color = ann_color.get(str(ann_id), None)
    tag = color_emoji.get(color, "〰️")  # 〰️ for underlines
    lines.append(f"{tag} {text}")
    lines.append("")

Annotation Data Structure

From describe_annotation:

{
  "id": 2133,
  "selected_text": "be impeccable with your word",
  "representative_text": "The first agreement is to be impeccable...",
  "note": null,
  "is_underline": 0,
  "style": 4,
  "color": "PINK",
  "chapter": null,
  "location": "epubcfi(/6/12[c005]!/4/10,/1:26,/2/1:28)"
}

Style-to-Color Mapping

Examples

Example 1: Export All Highlights from a Reading List

User says: "Extract highlights from the books in my reading list"

1. Read the user's list (file, note, etc.) to get book titles
2. list_all_books → match titles to IDs
3. For each matched book: get_book_annotations(book_id=ID) → collect annotation IDs + text
4. get_highlights_by_color x5 → build color map
5. Python script combines annotations + colors → writes .md files per book

Example 2: Search for a Quote Across All Books

User says: "Find where I highlighted something about shadow work"

1. search_highlighted_text(text="shadow") → returns matching annotations with book context
2. If color needed: describe_annotation(annotation_id=ID) for the few results

Example 3: Get All Pink Highlights

User says: "Show me all my pink highlights"

1. get_highlights_by_color(color="PINK") → all pink highlights across library
2. Group by book title for readability

Troubleshooting