weread-mcp
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- AlicenseNot gradedqualityCmaintenanceExposes the WeRead (WeChat Reading) gateway over Streamable HTTP so any remote MCP client can search the store, browse the shelf, read progress and statistics, pull highlights, personal thoughts and public reviews, and even read a full imported book's text and write AI annotations on a shared co-reading board. Requires only a URL and bearer token, letting phone apps use it without running any local process.MIT
- AlicenseNot gradedqualityCmaintenanceA remote Streamable HTTP MCP server that exposes WeChat Reading (微信读书) gateway capabilities — bookshelf, book search, details/chapters, reading progress and statistics, personal highlights and thoughts, public reviews, best bookmarks, and recommendations. It also adds a co-reading layer where the AI can read an imported book's original text by segment and write its own annotations to a paired dashboard, alongside one-click syncing of the user's own WeChat Reading highlights and notes.143 npmMIT
- FlicenseAqualityFmaintenanceAn MCP server enabling LLMs to access WeChat Reading bookshelf, notes, highlights, and reviews via tools like get_bookshelf, search_books, and get_book_notes_and_highlights.4176 npm171-
- AlicenseNot gradedqualityCmaintenanceEnables AI assistants to query a user's 微信读书/WeRead library over Streamable HTTP — bookshelf, reading stats, book details, highlights, personal notes, public reviews, and recommendations. It also powers a co-reading annotation board where the model can read imported EPUB text and write its own annotations alongside the user's.MIT
- AlicenseNot gradedqualityAmaintenanceEnables sandbox-less frontends such as mobile apps to reach the WeRead official gateway over Streamable HTTP by supplying only a URL and an access token, with no local process required. Exposes 14 read-only tools covering search, shelf, notebooks, reading progress and statistics, highlights, public reviews, and recommendations, plus a token-protected dashboard for shelf, notes, and shared-reading annotations.2MIT
- AlicenseBqualityAmaintenanceEnables MCP-compatible AI clients to read local WeChat data through an existing WxLens HTTP service, so users can find messages, extract a person's statements, summarize discussions, scan multiple groups, and read related articles or attachments.404MIT
TDQS
Scored across 19 tools
Most tools map cleanly to distinct API endpoints or user workflows, but the review/highlight cluster (get_book_highlights, get_best_highlights, get_highlight_reviews, get_my_reviews, list_book_reviews, get_review_detail) creates some overlap risk. The detailed descriptions do a good job of separating them, so misselection should be rare.
The dominant get_/list_/search_ snake_case pattern is consistent and readable. Minor deviations exist—recommend_books and similar_books lack a get_/list_ prefix, and get_reading_progress vs get_read_stats uses inconsistent root wording—but these do not seriously hinder prediction.
19 tools is on the heavier side, but each one covers a meaningful facet of the WeChat Reading domain: discovery, shelf, progress, highlights, reviews, stats, and recommendations. The two gateway-level meta tools add some noise but serve a legitimate fallback purpose.
The tool surface covers the core read-only workflows well: searching books, viewing shelf/progress, exporting highlights and reviews, pulling reading statistics, and getting recommendations. Mutating actions like adding to shelf or updating progress are absent, but they are likely outside the API's scope, and call_gateway provides a raw escape hatch for missing endpoints.