Goodreads Book Reviews Scraper

App Stores & Reviews

Operated by Sourcelane✓ verified

A web scraper that extracts structured review data and book-level metadata from Goodreads book review pages. The connector produces one record per review containing the full review text (may include simple HTML), star rating (1–5 or null), reviewer identity and profile link, reviewer avatar, review timestamp, engagement metrics such as likes and reply counts, reviewer-assigned shelves/tags, book title/author identifiers, and a scrape timestamp. It also produces a separate book metadata record with bibliographic identifiers, title and author details, description, aggregate ratings and counts, page count, publisher and publish date, language, genre tags, cover image link, series information, and the book page URL. The scraper supports sorting by recency or popularity, handles paginated review lists, and does not require login.

Verified Sep 28, 3:55 AM

$0.005

per result

Up to 100 per call. Only pay for results returned; failed calls are refunded.

What people use it for

Market research — analyse sentiment and themes across thousands of book reviews
Author / publisher monitoring — track new reviews and ratings on titles
Recommendation engines — pull labeled review results for machine learning training
Competitor analysis — compare reception of similar titles within a genre
Editorial discovery — find the most-liked review for a book to surface as a quote

Trust & reliability

7d uptime trend

Window	Uptime	Success rate	p50	p95
24h	—	—	—	—
7d	—	—	—	—
30d	—	—	—	—

Calling contract

Call it through Sourcelane's gateway or MCP server. We run the connector, apply your agent's spend guardrails, and bill only the results returned.

Call it via Sourcelane

curl -X POST https://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"goodreads-reviews-scraper","params":{"book":"3735293","maxItems":5},"maxResults":10}'

Request params

Field	Type	Required	Description
`book`	string	required	Goodreads book URL, numeric book ID, or ISBN (10 or 13 digit). Examples: 'https://www.goodreads.com/book/show/3735293-clean-code', '3735293', '9780132350884'.
`maxItems`	integer	optional	Maximum number of reviews to return. Set 0 for unlimited (stops ~60s before connector timeout). Capped at 100 per call.
`sortBy`	string	optional	Order in which reviews are fetched. 'most_liked' returns the popular/default Goodreads ordering.
`pageId`	string	optional	Optional. Paste NEXT_PAGE_ID from the previous run's Key-value store to fetch the next page.

Each result contains

Field	Type	Description
`reviewId`	string	Review Id
`url`	string	Url
`rating`	integer	Rating
`text`	string	Text
`reviewer`	string	Reviewer
`reviewerProfileUrl`	string	Reviewer Profile Url
`reviewerAvatarUrl`	string	Reviewer Avatar Url
`reviewDate`	string	Review Date
`likeCount`	integer	Like Count
`commentCount`	integer	Comment Count
`shelves`	array	Shelves
`bookTitle`	string	Book Title
`bookAuthor`	string	—
`bookId`	string	—
`scrapedAt`	string	—

Use Goodreads Book Reviews Scraper from Claude, ChatGPT or Cursor

Pick your tool and connect in under a minute. Then just ask — for example: “Summarise the one-star reviews for our iOS app from the last 30 days by theme.”

Connect Claude

Web, desktop and mobile. Paste one URL.

1Copy your personal connector URL
2In Claude open Settings → Connectors → Add custom connector
3Paste the URL and click Add — done

Manual setup (config files, REST, Python) +

Claude Code

Adds the Sourcelane MCP server with your key as a header.

terminal

claude mcp add --transport http sourcelane https://api.usesourcelane.com/mcp \
  --header "Authorization: Bearer sl_live_your_agent_key"

Claude Desktop (config file)

Alternative to the connector URL: add to claude_desktop_config.json, then restart Claude.

claude_desktop_config.json

{
  "mcpServers": {
    "sourcelane": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://api.usesourcelane.com/mcp",
        "--header",
        "Authorization:${AUTH_HEADER}"
      ],
      "env": {
        "AUTH_HEADER": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

Cursor & Windsurf

Add to ~/.cursor/mcp.json (or Windsurf's mcp_config.json).

mcp.json

{
  "mcpServers": {
    "sourcelane": {
      "url": "https://api.usesourcelane.com/mcp",
      "headers": {
        "Authorization": "Bearer sl_live_your_agent_key"
      }
    }
  }
}

VS Code

Save as .vscode/mcp.json. VS Code prompts for your key once.

.vscode/mcp.json

{
  "servers": {
    "sourcelane": {
      "type": "http",
      "url": "https://api.usesourcelane.com/mcp",
      "headers": {
        "Authorization": "Bearer ${input:sourcelane-key}"
      }
    }
  },
  "inputs": [
    {
      "type": "promptString",
      "id": "sourcelane-key",
      "description": "Sourcelane agent key",
      "password": true
    }
  ]
}

ChatGPT Custom GPT (Actions)

Create a GPT → Actions → Import from URL, then Authentication: API Key, Bearer.

OpenAPI schema URL

https://usesourcelane.com/openapi.json

REST

One POST. Pass maxResults to cap cost.

curl

curl -X POST https://api.usesourcelane.com/v1/call \
  -H "Authorization: Bearer sl_live_your_agent_key" \
  -H "Content-Type: application/json" \
  -d '{"listing":"goodreads-reviews-scraper","params":{"book":"3735293","maxItems":5},"maxResults":10}'

Python, LangChain, CrewAI, OpenAI Agents SDK…

Wrap the REST call as a tool, or point an MCP client at the endpoint.

python

import requests

res = requests.post(
    "https://api.usesourcelane.com/v1/call",
    headers={"Authorization": "Bearer sl_live_your_agent_key"},
    json={
        "listing": "goodreads-reviews-scraper",
        "params": {"book":"3735293","maxItems":5},
        "maxResults": 10,
    },
    timeout=300,
)
body = res.json()
print(body["receipt"]["chargedMicros"], "micro-USD for", body["receipt"]["results"], "results")
print(body["data"])

Reviews

—

0 reviews

Leave a review

Loading reviews…