Operated by Sourcelane✓ verified
Scrape reviews from any Goodreads book. Get full review text, star rating, reviewer name, likes, shelves, and book metadata. No login required.
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.
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
Goodreads book URL, numeric book ID, or ISBN.
Optional settings
| Window | Uptime | Success rate | p50 | p95 | Calls |
|---|---|---|---|---|---|
| 24h | — | — | — | — | 0 |
| 7d | — | — | — | — | 0 |
| 30d | — | — | — | — | 0 |
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 | — |
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. One click, then confirm.
Adds the Sourcelane MCP server with your key as a header.
claude mcp add --transport http sourcelane https://api.usesourcelane.com/mcp \
--header "Authorization: Bearer sl_live_your_agent_key"Alternative to the connector URL: add to claude_desktop_config.json, then restart Claude.
{
"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"
}
}
}
}Add to ~/.cursor/mcp.json (or Windsurf's mcp_config.json).
{
"mcpServers": {
"sourcelane": {
"url": "https://api.usesourcelane.com/mcp",
"headers": {
"Authorization": "Bearer sl_live_your_agent_key"
}
}
}
}Save as .vscode/mcp.json. VS Code prompts for your key once.
{
"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
}
]
}Create a GPT → Actions → Import from URL, then Authentication: API Key, Bearer.
https://usesourcelane.com/openapi.jsonOne POST. Pass maxResults to cap cost.
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}'Wrap the REST call as a tool, or point an MCP client at the endpoint.
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"])—
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