# Catalo.ai - Book Discovery

> Use this tool when you need to discover new books that match your specific preferences, such as mood, theme, pacing, or genre, and get personalized recommendations without relying on vague or popular suggestions. Catalo.ai's AI-curated book catalog allows you to search by unique filters, find lesser-known titles, and create a reading list with personal notes that your AI can analyze. Use it to explore books, manage your reading list, and gain insights into your reading habits through natural language queries.

Canonical page: https://skillsregistry.net/skills/catalo-ai-catalo  
JSON: https://api.skillsregistry.net/v1/skills/catalo-ai-catalo

## Description

## Find Books You'll Actually Finish

You know what you like in a book,\
You just haven't had a good way to search for it.\
*Until now...*

[Catalo.ai](https://catalo.ai) is an AI-curated book catalog built for readers who are tired of vague recommendations.
Search by mood, theme, pacing, genre, and more — without hallucinated titles or the same 10 books everyone already
knows.

### What you can do here that you can't do anywhere else

- **Search by vibe, not just genre** — filter by mood, theme, pacing, writing style, and atmosphere in combination. Ask
  for "slow-burn, atmospheric, cold setting, not action-heavy" and get real results.
- **Find lesser-known titles** — the catalog is curated to surface books beyond the usual bestseller lists and
  algorithmic "if you liked X" suggestions.
- **No hallucinated titles** — general-purpose LLMs frequently invent books that don't exist. Every result in Catalo is
  a real book from a real, curated catalog.
- **Natural language discovery inside your AI client** — find books mid-conversation without switching apps or tabs.
- **A reading list your AI can reason over** — bookmark books with personal notes, then ask your AI to analyze your
  habits across what you've finished, dropped, or want to read next.
- **Explore the search space itself** — ask what filters exist and what values are valid; the catalog's own structure is
  queryable.

---

## Suggested Prompts

**Discovery**

- *"Find me a slow-burn literary thriller set in a cold, remote location — something atmospheric, not action-heavy."*
- *"I want a fantasy novel that isn't epic in scale — more intimate, character-driven, maybe bittersweet."*
- *"Recommend some lesser-known sci-fi from the 70s or 80s with a philosophical bent."*
- *"I loved the vibe of Piranesi — find me something with that same dreamlike, uncanny feeling."*

**Using filters**

- *"What moods and themes can I filter books by?"*
- *"Show me all the pacing options available, then find me something fast-paced and tense."*

**Bookmarks**

- *"Show me all the books I've bookmarked but haven't started yet."*
- *"Bookmark that last book and add a note: recommended by my sister."*

**Statistics**

- *"Analyze the books I've read, want to read, and the books I've dropped, then give me insights into my reading
  habits."*

---

## Links

- **Website:** [catalo.ai](https://catalo.ai)
- **MCP Endpoint:** [catalo.ai/mcp](https://catalo.ai/mcp)

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-24

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-24

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/catalo-ai/catalo)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "catalo-ai-catalo"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/catalo-ai-catalo` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/catalo-ai-catalo/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt