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304,954 tools. Last updated 2026-07-22 14:31

"Researching an author based on their books" matching MCP tools:

  • Look up PubMed IDs from partial bibliographic citations. Useful when you have a reference (journal, year, volume, page, author) and need the PMID — deterministic citation matching, more reliable than free-text search for structured references. Each citation must include at least journal or year (ECitMatch primary-keys on journal+volume+page; author-only or volume-only inputs guarantee no match); more fields = better match accuracy.
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  • RETURNS A LIST OF BOOKS (works on a topic) — NOT passages. PICK THIS to discover which works exist on a subject. → For quotable text use search_translations (exact words) or search_concept (by meaning); if the user already named an author/work, call get_book directly (or list_books to find the ID) — the AI summary + chapter outline is usually the right first answer. Searches titles, authors, subjects, and (as a secondary signal) translated text. Query tips: single distinctive words or short phrases work best ("memory palace", "ouroboros"); quoted phrases match exactly. Each result includes total_matches (full count) + returned (this page) + offset for pagination.
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  • Start exporting the user's saved LinkedIn posts to a JSON file (a structured backup). Use this when the user asks to export/download/back up their saved posts as JSON. By default it exports the WHOLE library; to scope it, pass post_ids for a specific selection, or a filter (search_query, filter+value e.g. author/label/type, tags, or author). This records the export — it does NOT return the file. ALWAYS tell the user the export has started and to open the Export Center link (returned in the message) to view and download it.
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  • Start exporting the user's saved LinkedIn posts to a CSV (spreadsheet) file. Use this when the user asks to export/download their saved posts as CSV or to a spreadsheet. By default it exports the WHOLE library; to scope it, pass post_ids for a specific selection, or a filter (search_query, filter+value e.g. author/label/type, tags, or author). This records the export — it does NOT return the file. ALWAYS tell the user the export has started and to open the Export Center link (returned in the message) to view and download it.
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  • Propose a themed collection of books to the Source Library team — a title, a rationale (why these books belong together and what thread connects them), and an ordered list of book ids. Get book ids from search_library / list_books / get_book. Like submit_feedback and share_findings, this goes to the team for REVIEW — it does NOT create a public collection instantly; a curator reviews and approves it. Use this when the user has identified a coherent set of books worth grouping and wants to contribute that curation back.
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  • Search academic papers, books, and datasets via Crossref. For "search works titled X" / finding a SPECIFIC paper by its title, pass `title` (title-scoped — ranks the exact paper first). Beyond keyword search you can SORT by citation count or publication date and FILTER by date range, work type, and author — e.g. "most-cited papers on transformers" (sort=citations), "papers on LLMs since 2024" (from_date=2024-01-01), "recent journal articles by an author". Returns titles, authors, journal, DOIs, citation counts, and dates.
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Matching MCP Servers

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    maintenance
    A safety-gated MCP server for Zoho Books that enables AI agents to perform general-ledger writes, bank-feed categorization, and receipt attachments not exposed by Zoho's native connector, with hard guardrails preventing unauthorized actions on live data.
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    MIT

Matching MCP Connectors

  • RETURNS QUOTABLE PASSAGES matched by MEANING (cosine similarity on Gemini embeddings, 768d) — paraphrases and adjacent phrasings match even with zero keyword overlap. PICK THIS when the modern term won't literally appear in historical texts — e.g. "distributed cognition" maps to passages about active intellect, art of memory, wax tablet metaphors; "social contract" maps to pre-Hobbesian discussions of consent and authority. → For exact words/distinctive terms use search_translations (cheaper, more precise); to list which BOOKS cover a topic use search_library; if the user named an author/work, get_book first (semantic search is expensive — reserve it for cross-corpus discovery). Similarity calibration: 0.70+ is a strong match, 0.55–0.70 is worth reading but verify, below 0.55 is mostly conceptual drift. Set max_per_book to diversify results across many books rather than cluster on one source. Each passage carries a snippet_type — quote only "translation" snippets, never "summary". Cross-cultural tip: for pre-modern or non-Western topics, also try source-tradition vocabulary — e.g. for seminal economy try "jing preservation" or "bindu yoga" or "istimnāʾ"; for masturbation try "mollities" (Latin) or "hastamaithuna" (Sanskrit) or "shouyin" (Chinese). The corpus is indexed via period translations that use tradition-internal terminology, so adjacent/euphemistic terms often surface material that modern English keywords miss.
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  • Disambiguate an author name to a verified ORCID iD. Returns ranked candidates (5 by default, up to 20 via the rows parameter) with transparent disambiguation signals: name match type (exact/partial/other-name/none), institution overlap flag, and whether a DOI or PMID anchor was used in the query. A DOI or PMID anchor is near-deterministic — it filters to researchers who have linked that specific work to their ORCID record. Use this tool (not orcid_search_researchers) when the input is an ambiguous name that needs ranked disambiguation. No synthetic scores are used — raw signals only.
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  • Start (or resume) Stripe Connect onboarding so this account can RECEIVE author royalties. Returns a one-time onboarding_url the human author must open in a browser to complete KYC. Required before a book can be published: an author with no payouts-enabled Connect account can save drafts but their books stay in draft until onboarding finishes. Payouts stay disabled until Stripe verifies the details — poll connect_status afterward.
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  • Browse the most-downloaded Project Gutenberg books, ordered by popularity. Returns up to 32 titles with their Gutenberg IDs, authors, languages, and download counts. Optionally filter by language or topic. Use this as a discovery entry point — "what are the most popular classics in French?" — or as a heartbeat check that the catalog is reachable.
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  • Credit a patron's ledger from a BTCPay-settled invoice. **RESTRICTED to the operator** — the operator owns the books and is the only party who can issue a manual credit grant. Patrons who believe they paid but never got credits must escalate to the operator's support, who then invokes this tool on their behalf. Use cases: cold-start vault races during check_payment, ncred delivery hiccups, patrons closing Top-Off sheets before settle, any infrastructure incident that left an invoice settled at BTCPay but uncredited on the operator's ledger. Idempotent — if the invoice is already credited (in the patron's ``credited_invoices``), returns success with credits_granted=0.
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  • Credit a patron's ledger from a BTCPay-settled invoice. **RESTRICTED to the operator** — the operator owns the books and is the only party who can issue a manual credit grant. Patrons who believe they paid but never got credits must escalate to the operator's support, who then invokes this tool on their behalf. Use cases: cold-start vault races during check_payment, ncred delivery hiccups, patrons closing Top-Off sheets before settle, any infrastructure incident that left an invoice settled at BTCPay but uncredited on the operator's ledger. Idempotent — if the invoice is already credited (in the patron's ``credited_invoices``), returns success with credits_granted=0.
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  • Credit a patron's ledger from a BTCPay-settled invoice. **RESTRICTED to the operator** — the operator owns the books and is the only party who can issue a manual credit grant. Patrons who believe they paid but never got credits must escalate to the operator's support, who then invokes this tool on their behalf. Use cases: cold-start vault races during check_payment, ncred delivery hiccups, patrons closing Top-Off sheets before settle, any infrastructure incident that left an invoice settled at BTCPay but uncredited on the operator's ledger. Idempotent — if the invoice is already credited (in the patron's ``credited_invoices``), returns success with credits_granted=0.
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  • BROWSES/FILTERS THE CATALOG by metadata (author/title fragment, language, category, translation recency) — no content/topic matching. PICK THIS to see WHAT EXISTS by an author or in a tradition. Returns books with title, author, language, year, and translation progress. → For a relevance-ranked topic search use search_library; for passages on a theme use search_translations (exact words) or search_concept (by meaning).
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  • Start a shared GROUP trip-planning session that friends join by share code — the multi-user counterpart to pricetik_trip_plan. Pass destination (plus optional checkIn/checkOut/title). Returns the session, a shareCode, and a shareUrl (pricetik.com/trips/<code>) — give BOTH to the user so companions can join from their own agent (pricetik_group_trip_join) or vote on the web page without one. Choreography: create → search hotels/activities/tickets as usual → pricetik_group_trip_add_option for the strongest candidates → members vote → organizer finalizes. The creator becomes the session organizer. Requires an authenticated API key; pass an Idempotency-Key header to make retries safe. Sessions are coordinate-only — booking stays per-traveler via the booking-url tools; PriceTik never books on anyone's behalf.
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  • Add a label to a FEW explicitly chosen posts (specific post_ids the user picked or is looking at). Either label_id or label_name must be provided. NEVER use this to label 'all posts matching a filter' (a date range, an author, a tag, unread…) — fetched lists are ONE PAGE, so labeling their ids silently misses the rest; use tag_bookmarks_by_filter instead, which labels EVERY match server-side in one call and returns matched/tagged counts.
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  • Start exporting the user's saved LinkedIn posts to PDF. Use this when the user asks to export/download/back up their saved posts as a PDF (e.g. 'export all my saved posts to PDF', 'give me a PDF of my saved AI posts'). By default it exports the WHOLE library; to scope it, pass post_ids for a specific selection, or a filter (search_query for a keyword, filter+value e.g. author/label/type, tags, or author). This kicks off an async job — it does NOT return the file. ALWAYS tell the user the export has started and to open the Export Center link (returned in the message) to view and download it once ready; large exports can take up to a minute.
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  • Full metadata for one Flevy item, by content_id from search_content (e.g. "doc-1234" or "case-567"). Documents return the author with their credentials (headline, bio, LinkedIn, profile URL; pass the author name to search_content's author filter to list more of their documents), full description, editor summary, AI summary, and editorial review when available, page/slide count, price, FlevyPro inclusion, management topics, ranking badge, and the number of slide deep dives available. Case studies return the client situation, TL;DR, and summary. Call this before recommending an item so you can describe it accurately and cite the author's credentials, and share the returned flevy.com URL.
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  • RETURNS QUOTABLE PASSAGES (page-level snippets + citation URLs), matched by KEYWORD/term. PICK THIS to find a quote or textual evidence on a topic across the whole library. → If the modern word won't literally appear in historical texts, use search_concept (matches by meaning); to list which BOOKS cover a topic use search_library; to dig inside one known book use search_within_book; if the user named an author/work, get_book first (its AI summary is usually the right first read). Query tips: single distinctive terms ("memory palace", "wax tablet") work best; multi-word natural-English queries ("unity of the intellect") may return fewer results because matching is term-based, not phrase-based. Each snippet has a snippet_type — "translation"/"ocr" means it is a verbatim extract from the source text; "summary" means it is AI-generated description (do not quote those as the author's words). Response includes total_matches, returned, and offset for pagination. Cross-cultural tip: for pre-modern or non-Western topics, search source-tradition vocabulary rather than modern English terms — e.g. for seminal economy search "jing" or "bindu" or "istimnāʾ", not "semen retention"; for female homoeroticism search "tribade" or "sahq", not "lesbian". The corpus is indexed via period translations that use tradition-internal terminology.
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  • Search LibriVox authors by last name or keyword; supports pagination via limit/offset. Returns author id, first/last name, and a link to their LibriVox profile.
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