
Goodreads MCP
io.github.Danathar由 GitHub 帳號 Danathar 發布v2026.11.0更新於 Nov 7, 2026
Read-only MCP server for Goodreads (no API required): search, books, shelves, ratings
概覽
唯讀的 MCP 伺服器,讓助理不需 API 金鑰即可搜尋 Goodreads,並查詢書籍、評分、書評、版本、系列與公開書櫃。
- 可以做什麼
- 搜尋書籍,並取得書籍詳情、評分分布、所屬系列與各種識別碼
- 分頁讀取讀者書評,可依評分、語言、排序與劇透篩選
- 探索相關書籍:相似書籍、作者著作清單、系列閱讀順序、版本與 Listopia 書單
- 依年份或月份尋找熱門書籍,並依評分比較最多十本書
- 讀取公開使用者的書櫃與書櫃名稱,使用者 ID 可逐次傳入或設為預設
- 適用情境
- 適合讓助理研究某本書、作者或系列,蒐集讀者評價與書評,或查看某個公開 Goodreads 書櫃上的內容,且不需登入或持有 API 金鑰。
- 執行需求
- 以本機 Python 套件執行(需 Python 3.11 或更新版本),例如透過 uvx goodreads-mcp-ai 或 Claude Desktop 安裝包啟動。需要能連上 Goodreads 的網路。可選擇設定 GOODREADS_USER_ID 或設定檔,為書櫃工具提供預設使用者。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Goodreads MCP,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
[CI] [Nightly compliance] [Ask DeepWiki] [Maintenance assisted by Hivecommons Hive] [ACMM L6 Fully Autonomous] [AI assisted] [License: GPL-3.0]
📚 goodreads-mcp
Thank you, Shreeya Chand. This project is a fork of
shreeyachand/goodreads-mcp, and it would not exist without that work. The core idea of reaching Goodreads without its retired API, and the tool set this server offers, come from Shreeya's project. We're grateful for it, and for the MIT licence that let us build on it. If this server is useful to you, please go star the original.
A read-only MCP server for Goodreads — built without the Goodreads API, because there hasn't been one since December 2020. Lets an LLM find and research books, ratings, and reviews. Tools ride on the JSON autocomplete endpoint, the __NEXT_DATA__ blob embedded in book pages, the AppSync GraphQL backend the Goodreads website itself uses, and the shelf RSS feed, which Goodreads has answered with 404 for every user since Oct 2026. No login, no cookies, no writes — public data only.
tools
Every tool is registered with MCP read-only annotations (read-only, non-destructive, idempotent).
The discovery tools all take a book_id and return results carrying book_id/title/author/rating/url, so an agent can chain them — e.g. similar_books → get_reviews on a recommendation. book_id is a string on both sides ("54493401", or the slug form "54493401-title" on input), so a value copied out of one result is accepted as-is by the next call. average_rating is a number (or null) in every tool, so results from different tools sort together. This is the structured book graph a general web search can't assemble.
The five paginated discovery tools (similar_books, author_books, series_books, get_editions, book_lists) page in batches of 20 and accept a total limit up to 100; popular_books caps limit at 50. Responses include returned and has_more, keeping larger lookups useful without allowing unbounded traffic.
WAF and login note: Goodreads book HTML pages now sit behind an AWS WAF JavaScript challenge (HTTP 202) that plain HTTP clients can't solve.
get_bookroutes around it via the.xml-suffixed page, so it still works without a browser. If Goodreads ever extends the WAF to a path we depend on, the client raisesWAFChallengewith a clear message instead of a confusing parse error. The review-list page (/review/list/{uid}) became login-only in Sep 2026; the client raisesLoginRequiredon a sign-in redirect for the same reason, andlist_shelvesreads the public profile page instead.
install
With pip:
Or with uv, which is also what the Claude Desktop bundle uses:
Requires Python ≥ 3.11.
Each date-numbered release is also published to PyPI as goodreads-mcp-ai (the goodreads-mcp name there belongs to an unrelated project) and listed on the official MCP registry as io.github.Danathar/goodreads-mcp-ai, from server.json. The listing carries a uvx runtime hint; a client that follows it runs uvx goodreads-mcp-ai, which you can also run yourself.
config (optional)
No login or cookies — everything is public data. The only setting is your numeric user_id, the default for the shelf tools. It's the number in goodreads.com/user/show/<ID>-yourname; you can also pass user_id to each shelf tool per call.
Env var GOODREADS_USER_ID overrides the file. A config file that can't be read, isn't valid JSON, isn't a JSON object, or has a user_id that is neither a string nor a whole number is ignored with a warning on stderr (a bare number such as 12345678 is accepted and used as its string form; booleans, floats, lists and objects are ignored); the server still starts.
Claude Desktop config
Bundle. Each release carries a goodreads-mcp.mcpb. Releases come out monthly when the server itself changed, numbered by date (2026.10.0, 2026.10.1, 2026.11.0); 0.1.1 was the last of the old numbering, and every date-numbered release is newer than it. See CONTRIBUTING.md for how one is cut. Open the .mcpb in Claude Desktop to install. The bundle ships no dependencies — the manifest launches the server with uv run, and the host resolves pyproject.toml into a private environment on first launch — so one bundle runs on macOS, Windows and Linux with any Python ≥ 3.11. The bundle's optional "Goodreads User ID" setting (user_config.goodreads_user_id) is passed to the server as GOODREADS_USER_ID; left empty, it is passed as an empty value, and the server falls back to the config file.
Manual. Add the server to claude_desktop_config.json — on macOS ~/Library/Application Support/Claude/claude_desktop_config.json, on Windows %APPDATA%\Claude\claude_desktop_config.json; in any version, Settings → Developer → Edit Config opens it:
Or for development, mcp dev goodreads_mcp/server.py gives you the Inspector UI to poke each tool.
first-run verification
The endpoints are unofficial, so verify in this order:
search_books("project hail mary")— should just workget_book("54493401")— confirms the.xml/WAF workaround; check the histogram is populatedget_reviews("54493401")— should return real review textget_shelf("to-read")— raisesShelfFeedUnavailablewhile Goodreads answers the shelf feed with 404 (since Oct 2026); that is not auser_idproblemlist_shelves()— best-effort shelf-name scrape
For an end-to-end example that chains the tools, see prompts/research-a-book.md.
tests
The offline suite runs on fixtures; CI runs it with pytest-cov and enforces a coverage floor (--cov-fail-under in ci.yml). The live smoke tests are in tests/e2e/test_smoke_live.py and skip unless GOODREADS_LIVE=1 is set. The nightly compliance run runs the live suite against the real endpoints every night, so upstream drift shows up within a day.
documentation
- docs/design.md — design notes: the data surfaces, WAF and login handling, politeness and concurrency
- docs/roadmap.md — ideas not built yet
- docs/maintenance.md — how this repository is maintained (Hive, ACMM L6, outreach PRs held for human review)
- docs/ai-ops-runbook.md — what to check and do for each automated signal
- docs/quality.md — what the tests and numbers do and do not prove
- docs/risk-tiers.md — the risk tier every pull request declares
- docs/review-rubric.md — the review checklist
- docs/metrics.md — outcome metrics
- docs/strategy.md — what the project is for, what it won't do, and the commands that say whether it is on track
- docs/reflections/ — lessons learned about this codebase
- docs/SECURITY-AI.md — what AI agents may and may not touch
about this project
[!NOTE] Work on this fork is done with AI assistance and should be treated cautiously.
This is a third-party tool. It is not an official Goodreads or Amazon product, is not sanctioned by either, and uses no official API — there hasn't been one since December 2020. "Goodreads" is a trademark of its owner and is used here only to say what this software talks to.
It reads public data only: no login, no cookies, no writes. It is provided as-is, with no promise that the endpoints it depends on will keep working or that using it is consistent with Goodreads' terms. Keep request volume modest. The maintainer is not responsible for rate limiting, blocking, data loss, or other consequences of using this software.
license
This fork is licensed under the GNU General Public License v3.0, version 3 only (GPL-3.0-only) — no automatic upgrade to later versions.
It incorporates code from shreeyachand/goodreads-mcp, Copyright (c) 2026 Shreeya Chand, released under the MIT License. That code remains under MIT; its licence text and copyright notice are preserved in LICENSE.MIT as the MIT licence requires. The combined work — upstream code together with this fork's changes — is distributed under GPL-3.0.
來源:README.md,提交 e22b3b0
工具
0版本歷史
4- v2026.11.0最新Nov 7, 2026
- v2026.10.0Oct 10, 2026
- v2026.9.3Sep 27, 2026
- v2026.9.2Sep 26, 2026
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