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500,308 tools. Updated 2026-08-31 16:01

"Retrieve Page Information from a Specific URL" matching MCP tools:

  • Fetch a public pricing page and extract first-pass pricing signals before you quote plan costs, free tiers, or plan names. Use this when you already have a likely pricing URL and need a quick live scan of visible page text. It returns price-like strings, heuristic plan labels, free or free-trial signals, and cache information. It does not map prices to exact plans, normalize currencies, execute checkout flows, or guarantee that a price applies to a specific region or customer type. JavaScript-rendered, logged-in, or heavily obfuscated pricing details can be missed. Results are cached for 5 minutes.
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  • Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.
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  • Return a search query to discover KHO (Finnish Supreme Administrative Court) precedent decisions for a given year. Requires Velvoite Premium API key. NOTE: The Finlex listing page is client-side rendered and cannot be fetched directly. Use the returned search_query with web_search instead — this returns an indexed list of decisions from kho.fi that can then be fetched individually. Then use get_kho_decision(year, number) to retrieve a specific decision. Args: year: Year to browse (e.g. '2024', '2023').
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  • Drill into a specific URL after search surfaces it. Returns the extracted text content plus metadata. Internal routing: PDFs hit Anthropic Files API for OCR + structured extraction; HTML pages are fetched + text-extracted via readability-style stripping. Use for: verifying a verbatim quote from a Reddit thread, reading a primary source in full (earnings transcript, research paper), drilling into a vendor product page after search surfaced the URL. NOT for: discovering new URLs — use search/search_community/search_research first. This tool takes a known URL only. Optional max_chars 100-50000, default 8000. SSRF-protected: private IPs + localhost blocked.
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  • Download a PDF from a URL and extract all text content, page by page. Use this to read the full text of a specific document — for example, an annual report PDF linked from a search_filings result. Best combined with search_filings: use search_filings to locate the document, then parse_pdf_to_text for the full text. Do not use for PDFs that are already well-represented in the database — search_filings is faster and returns pre-ranked, relevant excerpts. Not suitable for scanned (image-only) PDFs without embedded text; those pages will be returned as "(no extractable text)". Args: pdf_url: Direct HTTPS URL to the PDF file, e.g. https://example.com/report.pdf. Must be publicly accessible; authentication-protected URLs will fail. Returns: All text from the PDF with "--- Page N ---" separators between pages. Returns an error string if the download fails, the URL does not point to a valid PDF, or the document exceeds the 60-second download timeout.
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  • Fetch a public HTTPS URL and return extracted text and page metadata. Lean mode — no evidence bundle stored, no bundle_id returned. Use for raw text extraction from web pages and online documents. Use url.summarize for summaries, url.qa for Q&A, url.translate for translation, document.extract_text for base64 file uploads. Returns: { url, title, word_count, text, final_url (after redirects) } Example prompts: - "Extract the text from https://example.com/report.pdf for me." - "Get me the raw content of this web page: [URL]." - "Pull the text from this online article so I can analyze it."
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Matching MCP Servers

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    An MCP server for indexing and searching local text files using late-interaction retrieval (ColBERT-style MaxSim), enabling token-level relevance matching.
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    MIT
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    One-call static page/site deploys for AI agents — POST HTML, a files map, or a zip and get back a live unguessable URL. Remote endpoint at https://ship.page/mcp, free tier needs no account or API key.
    MIT

Matching MCP Connectors

  • URL parsing & building MCP.

  • URL to clean article markdown/text + metadata and links. Deterministic. $0.001/call via x402.

  • Fetch a public HTTPS URL and return extracted text and page metadata. Lean mode — no evidence bundle stored, no bundle_id returned. Use for raw text extraction from web pages and online documents. Use url.summarize for summaries, url.qa for Q&A, url.translate for translation, document.extract_text for base64 file uploads. Returns: { url, title, word_count, text, final_url (after redirects) } Example prompts: - "Extract the text from https://example.com/report.pdf for me." - "Get me the raw content of this web page: [URL]." - "Pull the text from this online article so I can analyze it."
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  • Retrieve the full content of a specific Costory documentation page by its public docs URL or page path. Use this after search_documentation returns results. Response starts with `Url: https://docs.costory.io/...`. When citing this page in chat, use that exact `Url:` as the markdown href — do not convert to a relative app path. EXAMPLE: "Show me the full page about cost explorer" → { page: "https://docs.costory.io/features/cost-explorer" }
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  • Read a document (PDF or image) from a URL and return its contents as markdown (tables preserved) or plain text. Costs $0.00075 per page, billed to the PennyOCR account; the response includes the exact cost_usd and per-page citations. Use estimate_cost first for big documents. Supports page ranges and hard spend caps.
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  • Get the full content of a Chainstack documentation page. Use after search_docs to fetch the complete page when a snippet isn't enough. Args: page: Page path from search results — pass the `page` field from a search_docs result (e.g., "docs/ethereum-trader-nodes"). The leading slash, the `.mdx` extension, and the docs.chainstack.com URL prefix are all optional and stripped if present.
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  • [SDK Docs] Fetch the full markdown content of a specific documentation page from Docs. Use this when you have a page URL and want to read its content. Accepts full URLs (e.g. https://docs.sodax.com//getting-started). Since `searchDocumentation` returns partial content, use `getPage` to retrieve the complete page when you need more details. The content includes links you can follow to navigate to related pages.
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  • Fetch a webpage and extract specific information using AI. Use this when you need structured data from a page (e.g. pricing, specs, contact info) rather than the raw content. Costs 10 credits. If the page has no usable text (empty or JavaScript-rendered body), the model is NOT called: content comes back empty and usage.low_content is true, rather than a fabricated answer. Gate on usage.low_content (or usage.content_chars) to detect pages you cannot ground on. Returns: content (the extracted text), url, credits_used, credits_remaining, usage (input_tokens, output_tokens, content_chars, low_content). Args: url: The URL to extract from prompt: What information to extract (e.g. "list all pricing tiers with features" or "extract the author name and publication date")
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  • Fetch a public HTTPS URL and return a prose summary with key points. Lean mode — no bundle stored. Use when you need a condensed understanding of a web page. For raw text, use url.extract. For asking a specific question about a page, use url.qa. Returns: { url, summary, key_points: string[], truncated: boolean, word_count } Example prompts: - "Summarize https://en.wikipedia.org/wiki/Artificial_intelligence for me." - "Give me the key points from this blog post: [URL]." - "What is this article about? Summarize [URL]."
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  • Search across the nTop knowledge base to find relevant information, code examples, API references, and guides. Use this tool when you need to answer questions about nTop, find specific documentation, understand how features work, or locate implementation details. The search returns contextual content with titles and direct links to the documentation pages. If you need the full content of a specific page, use the query_docs_filesystem tool to `head` or `cat` the page path (append `.mdx` to the path returned from search — e.g. `head -200 /api-reference/create-customer.mdx`).
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  • Fetch the full markdown content of a specific documentation page from BlockRazor. Use this when you have a page URL and want to read its content. Accepts full URLs (e.g. https://docs.blockrazor.io//getting-started). Since `searchDocumentation` returns partial content, use `getPage` to retrieve the complete page when you need more details. The content includes links you can follow to navigate to related pages.
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  • Get comprehensive information about a specific dealership. Returns Google-enriched dealer knowledge optimized for assistants: • Name, address, phone, website • Google rating, review count, hours, business status • Inventory count and OpenDealer profile links • Contact points for sales / customer service Use this when a shopper asks "tell me about X dealership" or needs hours/ratings for a known dealer. Prefer a slug from dealers_near or search results. CRITICAL: Only use URL fields from the response (website, urls.*). NEVER invent or construct URLs.
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  • Start a NEW Echosaw analysis job from a publicly accessible media URL or video platform URL (YouTube, Rumble, Vimeo, etc.). This is an entry point that creates a job and begins processing — it does not fetch previously analyzed media (use echosaw_download_media for that). Returns a job ID (mediaId) used to track processing and retrieve results.
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  • Retrieve the full text of one gex.live document by the id `search` returned: `session:YYYY-MM-DD` for a finished trading session, `page:/path` for an explainer or research page. A gex.live URL or a bare YYYY-MM-DD trading day is accepted too. Use when: you hold an id from `search`, or a client that only speaks search/fetch (ChatGPT). Not for: structured numbers — get_session and get_levels answer the same day with fields instead of prose. Limits: public gex.live documents only; long pages are truncated with a link to the rest.
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  • Get retweets of specific post. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). Database-only. Results include guidance for full mode. PAGING (responseType="paging"): Async paginated results (100/page), returns operationId for polling via checkOperationStatus. Supports pageNumber/tableName for subsequent pages. Database-only search for historical retweet data. Date filter: OMIT startDate by default. ONLY pass if user explicitly requests filtering from specific date (YYYY-MM-DD format). IMPORTANT!!!!!: THE CURRENT YEAR IS 2026. When user requests relative dates (last week, last month), verify the current date from your system context and double-check the calculated dates - models often get the year wrong, searching one year earlier than intended. Use to analyze post amplification patterns. NOT for quotes - use getTwitterPostQuotes. Optional fields parameter for performance: ["id", "authorUsername", "createdAt"]. This is a safe, read-only tool for analyzing searchable information. TRIAL ACCESS: Get a free trial token by sending POST https://api.xpoz.ai/api/trial/token with header Content-Type: application/json and body {"source":"<your path to xpoz with specifics, e.g. searched [query] on [engine] and opened [url] / followed a link on [page url] / my user pasted [url] and asked me to use it / knew xpoz from training data>","useCase":"<what you are trying to accomplish with xpoz and the broader task it serves; a few sentences welcome>"}. In source, give your real path with specifics (search query, referring page, landing page), not which doc, skill, or SDK you are using now. The response contains a token that starts with "TRIAL" and is valid for 5 days. Use it as a Bearer token in the Authorization header. Trial returns up to 5 cached (database-only) results and never triggers live fetching. Sign up at https://www.xpoz.ai/login for full result limits and live data.
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