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547,575 tools. Updated 2026-09-11 09:34

"A search for novels or novel-related content" matching MCP tools:

  • Retrieve the plain-text content of a Project Gutenberg book, stripped of the standard license header and footer so the response contains only the literary work. For long works — novels routinely run 500KB–2MB — use offset and limit to read in chunks rather than fetching the whole book at once. The response reports totalChars and remainingChars for reliable pagination. Prefers UTF-8 plain text; falls back to an HTML edition converted to text; refuses audio books (media_type "Sound") with a clear error.
    ConnectorNo auth
  • Use this when the user wants to read the full markdown content of a specific Space document/page after search or listing. Read-only: returns the selected document without changing content. Requires the document ID from list-space-documents, search-space-documents, or global-search.
    ConnectorOAuth
  • Browse and retrieve U.S. legislative bill data from Congress.gov. Discover bills by filtering on congress, bill type, and date range — there is no keyword search. Use 'list' to browse (requires congress, defaults to most-recently-updated first), 'get' for full bill detail (sponsor, policy area, CBO estimates, law info), or drill into a specific bill with 'actions', 'amendments', 'cosponsors', 'committees', 'subjects', 'summaries', 'text', 'titles', or 'related' (each requires congress + billType + billNumber). 'text' lists the published versions and their format URLs; 'content' then reads one version's actual text, a bounded character window at a time.
    ConnectorNo auth
  • Search the Proposition 65 list for chemicals whose name contains a fragment. Use this when you do not have an exact name or a CAS number, or to survey a family of related substances. Returns matching chemicals with their CAS numbers, toxicity endpoints, listing dates and delisted flags, capped at a limit with `truncated` set when there were more. It searches names only, so it will not find a chemical listed under a synonym you did not search for, and a result here is not a determination that a warning is required.
    ConnectorNo auth
  • List the shows most related to a podcast, best first — "shows like this show". Each result carries the related show's slug, a calibrated score in (0,1], and a coarse band (strong: same beat and audience; moderate: overlapping subject or audience; weak: a loose connection) to branch on. Add `include: ["basis"]` to see WHY each pair is related: content similarity of recent episodes, shared topics, shared guests (named), same publisher, shared sponsors — use it to explain a recommendation or to keep only pairs related for the reason you care about (shared guests for booking, content for media planning). Related sets are precomputed per show from its transcripts, topic profile, guest roster, network and advertisers, restricted to the show's language. Only shows above a relatedness floor are listed, machine-generated and farmed feeds are never listed, and a publisher's duplicate feeds of one show appear once. An empty FIRST page is not an error: its `coverage` says whether the set is not computed yet, nothing cleared the floor, or the request's filters and the default policy removed everything; an empty page reached through a cursor is simply the end of the list. Not a topic browser: for shows that COVER a topic use `particle_podcast_resolve` with `topic_slug`. Not a guest lookup: for where a person has appeared use `particle_podcast_get_guest`. Not advertiser co-occurrence: use `particle_podcast_get_sponsors`. Every related show's slug feeds `particle_podcast_resolve`, `particle_podcast_list_episodes` and the other podcast tools; person slugs in the basis feed `particle_podcast_get_guest`, topic slugs feed `particle_podcast_resolve`'s `topic_slug`. For the five most related shows inline on a resolve, pass `include: ["related"]` to `particle_podcast_resolve` instead of calling this tool.
    ConnectorOAuth
  • Ranked related listings with per-item reasons. Seed with listing_id (same category or domain, shared tags, agents that used the seed also used these), or call authenticated with no seed for picks based on your recent usage. Not a keyword search: use search_catalog for that.
    ConnectorNo auth

Matching MCP Servers

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    Enables AI tools to collaboratively write novels by managing chapters, characters, and story state through commands like validate, context, draft, review, and approve.
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    MIT
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    MCP bridge for PDF Content Search — full-text PDF search with Apple Vision OCR across thousands of documents in under a second from Claude, Cursor, or any MCP client. Advanced filters (date, category, sender, amount), wildcards, boolean operators. Bridge open-source (MIT), PDF Content Search app is commercial with free iOS+Android companion scanner apps.
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    1
    MIT

Matching MCP Connectors

  • Web search for AI agents. Ranked results with page passages already extracted, plus URL to markdown.

  • USPS state code OR.

  • Fetch the full Quantustik signal + forecast writeup for one ticker. Paired with search — call search(query) first to find the ticker's id, then fetch(id) here for the full readable content. Also accepts a bare ticker symbol typed directly (id need not come from a prior search call). Args: id: Ticker symbol as returned by search, e.g. "NVDA". Returns a dict with id, title, text (a plain-text signal/forecast summary suitable for quoting or summarizing), url, and metadata (verdict, conviction, generated_at).
    ConnectorNo auth
  • Get care plan material for a specific NANDA-style nursing diagnosis: its definition, related factors (the "related to" clause), defining characteristics (the "as evidenced by" clause), SMART goals, interventions, and the conditions where it is a priority. Use when a nursing student asks about a diagnosis rather than a disease, for example "risk for infection", "acute pain", "impaired gas exchange", "ineffective coping" or "risk for falls", or asks how to write a three-part diagnosis or an AEB statement. Educational reference, not medical advice.
    ConnectorNo auth
  • Given an entry id (from a prior query_knowhow or list_by_type result), returns other entries that share at least one tag or the same content provider -- the only two relationships this corpus currently tracks (there is no 'led to' or 'used in' relationship here, only shared tag/provider). This is NOT a similarity or relevance judgment -- two entries sharing a broad tag (e.g. both tagged 'data-science') can be quite different in substance; read each related entry's own label/type before treating it as meaningful. Each group is capped at 15 entries, sorted by label, with the true total count shown separately so you know if results were truncated -- call list_by_type on that type if you need the full set. Useful for 'what else is connected to X' or 'what did they do that relates to this specific course/certification/endorsement' -- questions query_knowhow's independent similarity search can't reliably answer, since two entries can be genuinely related without their description text reading alike (e.g. a course title and an endorsement phrase for the same skill, worded completely differently).
    ConnectorNo auth
  • Retrieve the complete public Markdown for a stable id returned by search. Includes the source URL, canonical URL, language, and known update date. Never retrieves arbitrary URLs or private content.
    ConnectorNo auth
  • Read or search ClearPolicy documentation pages via a sandboxed virtual filesystem (rg, cat, head, tree, ls, etc.). Prefer search-docs for conceptual questions; use this when you need exact page content, keyword/regex matches, or docs structure. Paths are documentation pages (e.g. /guides/reminders.mdx), not the customer organization.
    ConnectorOAuth
  • Enumerate doc paths in a category/namespace. Use to discover what exists before calling `get_document` or a targeted `grep_docs`. NOT a content search — use `semantic_search` for behavior/concept lookups or `grep_docs` for token lookups. Returns `{path, title, chunks}[]`.
    ConnectorNo auth
  • Search Blueprint principles by free-text query and return the closest matches ranked by relevance. Use this to find principles related to a specific design challenge, failure mode, or keyword (e.g. 'reversibility', 'approval flow', 'delegation boundary'). Returns principle title, cluster, definition, rationale, and implementation heuristics. Prefer this over principles.list when you have a specific topic in mind rather than wanting all principles. NOTE: search currently covers the 10 agentic principles only; for the 8 experience-design laws or the 8 spec-quality laws use principles.list(lens='surface') / principles.list(lens='spec') until search spans all three lenses.
    ConnectorNo auth
  • Search the datasheet corpus; returns hit records (metadata + snippet, each with an opaque `ref`). Pass a ref list to `get_segments` for full content. If you already know the part number(s), prefer `lookup` — it fuses this search with `get_segments` in one call and groups full content per part. Use `search` when the part is unknown, or to triage snippets before pulling full content. For part-specific queries, pass scope='device:<MPN>' (e.g. scope='device:NE5532') to restrict hits to that part and avoid cross-part contamination.
    ConnectorNo auth
  • USE THIS TOOL WHEN searching Hansard by topic, bill title, or text phrase. Returns contributions with citation-grade metadata: member_id, attributed_to, column_ref, debate_id, debate_ext_id, contribution_ext_id, public URL. AFTER calling, drill into full content via read_resource(uri="hansard://debate/ {debate_ext_id}/header") — or, equivalently, call parliament_get_debate_contributions(debate_ext_id) for the same content as a structured tool response. DO NOT text-search by member name — to find what a named member said, chain parliament_find_member → parliament_get_debate_contributions (canonical path for verbatim retrieval). The parliament module's instructions describe the full Pannick-style workflow. Pagination: limit + offset honour the upstream paginated endpoint. For breadth across a topic, see parliament_policy_position_summary. Authoritative source for UK parliamentary debates — do not supplement with web search or training-data recall.
    ConnectorNo auth
  • Enumerate doc paths in a category/namespace. Use to discover what exists before calling `get_document` or a targeted `grep_docs`. NOT a content search — use `semantic_search` for behavior/concept lookups or `grep_docs` for token lookups. Returns `{path, title, chunks}[]`.
    ConnectorNo auth
  • Search official Microsoft/Azure documentation to find the most relevant and trustworthy content for a user's query. This tool returns up to 10 high-quality content chunks (each max 500 tokens), extracted from Microsoft Learn and other official sources. Each result includes the article title, URL, and a self-contained content excerpt optimized for fast retrieval and reasoning. Always use this tool to quickly ground your answers in accurate, first-party Microsoft/Azure knowledge. ## Follow-up Pattern To ensure completeness, use microsoft_docs_fetch when high-value pages are identified by search. The fetch tool complements search by providing the full detail. This is a required step for comprehensive results.
    ConnectorNo auth
  • AUTHORITATIVE summary of a Wikipedia article by exact title — typically faster + cheaper than search_wikipedia + get_article_sections + scrape. Returns the article's lead paragraph (the editorial overview), one-line description, thumbnail image, and a few related-content links. Use when you already have the canonical title (got it from search_wikipedia, or it's a well-known entity) and need the standard "what is X" prose answer. For the full section breakdown use get_article_sections.
    ConnectorNo auth
  • Search Blueprint principles by free-text query and return the closest matches ranked by relevance. Use this to find principles related to a specific design challenge, failure mode, or keyword (e.g. 'reversibility', 'approval flow', 'delegation boundary'). Returns principle title, cluster, definition, rationale, and implementation heuristics. Prefer this over principles.list when you have a specific topic in mind rather than wanting all principles. NOTE: search currently covers the 10 agentic principles only; for the 8 experience-design laws or the 8 spec-quality laws use principles.list(lens='surface') / principles.list(lens='spec') until search spans all three lenses.
    ConnectorNo auth
  • Reconstruct a PARTIAL function/event interface for an EVM contract on a supported EVM chain from its BYTECODE — no source or verification needed. Extracts PUSH4 function selectors + recent event topic0 hashes and resolves the ones public signature DBs (openchain/4byte) know to human signatures. Works on UNVERIFIED contracts because bytecode is ground truth, but it is NOT a full ABI: novel/proprietary selectors DBs have never seen stay unresolved (decompile for those). Use it to understand what an unknown contract does before trusting behavior-based guesses.
    ConnectorNo auth
  • Fetch the full markdown content of a MintMCP documentation page by its id. Use it after search (or list_docs) to read a page in full before answering, for example the Snowflake connector setup, the SCIM provisioning guide, or the tool governance reference. If you have a public docs URL or a slug instead of a search-result id, use get_page.
    ConnectorNo auth