"Methods to Extract Text Content from Videos" matching MCP tools:

• parse_pdf_to_textA

  Nordic Financial MCPA

  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.

  ConnectorNo auth

• url.extractA

  DocImprintA

  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."

  ConnectorNo auth

• url.extractA

  apiA

  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."

  ConnectorNo auth

• web_url_readerA

  Inferventis MCP ServerA

  Fetches any public web page and returns clean, readable plain text stripped of HTML, navigation, scripts, advertisements, and boilerplate. Returns the page title, meta description, word count, and main body text ready for analysis or summarisation. Use this tool when an agent needs to read the content of a specific web page or article URL — for example to summarise an article, extract facts from a page, verify a claim by reading the source, or convert a web page into plain text to pass to another tool. Pass article URLs returned by web_news_headlines to this tool to read full article content. Do not use this tool to discover current news headlines — use web_news_headlines instead. Does not execute JavaScript — best suited for standard HTML content pages. Will not work with paywalled, login-protected, or JavaScript-rendered single-page applications.

  ConnectorNo auth

• rendex_extractA

  Rendex: Rendering API for Images, PDFs & Content ExtractionA

  Use this when the user asks to read, extract, get the text/content/article of, or summarize a webpage/URL. Do NOT use for a visual screenshot (use rendex_screenshot). Extracts clean reader-mode content from any webpage as Markdown, JSON, or HTML. Runs the same Chromium render pass as a screenshot, so it captures content after JavaScript runs — handles SPAs that fetch-only readers miss. Strips nav, ads, and boilerplate, returning the article body plus title, byline, and excerpt. Great for feeding page content to an LLM, summarization, or RAG ingestion. Costs 1 render credit per call.

  ConnectorNo auth

• niche_voice_profile_ingestA

  Niche — Editorial IntelligenceA

  Extract voice primitives (register / sentence rhythm / lexicon preferences / punctuation habits) from post-shaped text and persist onto the user's VoiceProfile. The voice primitives thread into content generation so generated copy matches the user's actual writing voice. Two input shapes: pass `posts` (list of pre-collected text snippets, ≥80 chars each) or pass `url` (the server scrapes post-shaped snippets from the page: Substack / Medium / blog / X profile). Inline posts win when both are given. Inline post-shaped snippets need to be the user's own writing, not press articles or marketing copy. Returns the extracted primitives + a diff of what changed on the stored VoiceProfile.

  ConnectorNo auth

• get_full_textA

  PubmedA

  Fetch the FULL TEXT of a biomedical paper from PubMed Central (the open-access subset) by PubMed ID. PREFER OVER get_abstract when you need methods/results/discussion, not just the abstract — "read the full paper", "what methods did <PMID> use", "extract details from the paper". Resolves the PMID to its PMC id and returns the article body text (capped ~40k chars). Only open-access articles are in PMC — returns has_full_text:false (use get_abstract) otherwise.

  ConnectorNo auth

• extractA

  SofyaA

  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")

  ConnectorNo auth

• document.extract_textA

  apiA

  Extract plain text from a PDF or image (base64-encoded). Use when you need raw text for downstream AI analysis (summarization, claim checking, structured extraction). For documents at a public URL, use url.extract instead (no base64 encoding needed). Returns: { pages: number, text: string } Example prompts: - "Extract the text from this scanned contract so I can search it." - "Give me the raw text from this PDF document." - "OCR this image and return the text content."

  ConnectorNo auth

• document.extract_tablesA

  apiA

  Extract tables and forms as Markdown from a PDF or image (base64-encoded). Use when the document contains structured tabular data such as financial statements, data sheets, or forms. For plain prose documents, use document.extract_text instead. Returns: { pages: number, text: string } — text contains Markdown-formatted tables. Example prompts: - "Extract the tables from this financial statement." - "Pull the data table from this PDF into Markdown format." - "Get the tabular data from this form document."

  ConnectorNo auth

• parse_addressA

  QinisoA

  USE THIS to extract structured {country, postcode, city, state} from a free-text UK or US address — when onboarding a user, running a KYC/fraud check, or storing an address — instead of splitting the string yourself. Returns a confidence flag.

  ConnectorNo auth

• fetch_structuredA

  Agent RescueA

  Fetch a public URL and return its content as JSON validated against the schema you pass. Use it when you need data from a page and cannot parse it reliably yourself. Do not use it for URLs requiring authentication or a session, for internal networks, or when you already have the content — extract it yourself in that case. `extracted_by` tells you where the answer came from: `structured_data` when the page already published it (JSON-LD, OpenGraph, or a JSON body — exact and free) or `model` when it had to be extracted from the text. If structured extraction is unavailable, the response carries `degraded: true`, `data: null` and the page `text` for you to parse: check `degraded` before reading `data`.

  ConnectorNo auth

• generate_contentA

  SendItB

  Generate AI-powered platform-optimized content without publishing. Uses AI to create platform-specific text, hashtags, and titles from a prompt or media URL. Respects brand voice profiles if configured. Returns generated content variants for each target platform. Use publish_content to publish the generated content, or publish_ai to generate and publish in one step.

  ConnectorNo auth

• tiktok_search_videos_listA

  Social FetchB

  Search TikTok videos by free-text keyword (not hashtag — use tiktok.search.hashtag.list for that). Returns a list (use cursor when paginated).

  ConnectorNo auth

• web_url_readerA

  Inferventis — Financial Data, News & Web MCPA

  Fetches any public web page and returns clean, readable plain text stripped of HTML, navigation, scripts, advertisements, and boilerplate. Returns the page title, meta description, word count, and main body text ready for analysis or summarisation. Use this tool when an agent needs to read the content of a specific web page or article URL — for example to summarise an article, extract facts from a page, verify a claim by reading the source, or convert a web page into plain text to pass to another tool. Pass article URLs returned by web_news_headlines to this tool to read full article content. Do not use this tool to discover current news headlines — use web_news_headlines instead. Does not execute JavaScript — best suited for standard HTML content pages. Will not work with paywalled, login-protected, or JavaScript-rendered single-page applications.

  ConnectorNo auth

• extractA

  TavilyA

  Extract clean article text from one or more URLs via Tavily: strips boilerplate/navigation and returns up to 20,000 chars of readable content per page. Accepts a single URL string or an array. Ideal for feeding source pages into an LLM.

  ConnectorNo auth

• mio_ai_clip_makerA

  MiOffice — AI-Powered Workspace StudioC

  AI Clip Maker — Extract the best short clips from long videos using AI. AI Studio run — dispatches to our AI workers (Modal). Credits per run vary by model and file size. Day Pass and welcome credits do not include AI Studio. Files are deleted after processing; auditable at mioffice.ai/account/tasks (retention details at mioffice.ai/privacy). All three credit-based workspaces unlock with the same one-time credit pack — there is no per-workspace subscription. See mioffice.ai/pricing for current plans.

  ConnectorNo auth

• list_assetsA

  agentViewA

  Lists the user's uploaded assets (images, videos, fonts, documents) with public URLs for use in display HTML. Filter by type, search term or group. Check before upload_asset to avoid duplicates. response_format 'detailed' adds description, size and timestamps per asset. Requires content scope.

  ConnectorNo auth

• document.extract_tablesA

  DocImprintA

  Extract tables and forms as Markdown from a PDF or image (base64-encoded). Use when the document contains structured tabular data such as financial statements, data sheets, or forms. For plain prose documents, use document.extract_text instead. Returns: { pages: number, text: string } — text contains Markdown-formatted tables. Example prompts: - "Extract the tables from this financial statement." - "Pull the data table from this PDF into Markdown format." - "Get the tabular data from this form document."

  ConnectorNo auth

• run_quality_checkA

  freedom-mcpA

  Evaluate content or media against your ICP persona using Gemini 3.1 Pro vision. Actually SEES images and WATCHES videos. Returns quality scores (1-10) across 6 dimensions + specific ICP feedback. Use after generating media or drafting content to validate quality before delivering to the user. [sensitive-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]

  ConnectorNo auth

• get_videoA

  canton-ccpediaA

  Get a Canton Network video that CCPEDIA has cached (curated channels: Canton Network, Digital Asset, Sync Insights, Canton Foundation, Daml) by its YouTube id: title, channel, publish date, description and full transcript text if stored. CANTON-ONLY and limited to videos already in CCPEDIA's index. Does NOT fetch arbitrary YouTube videos (use a dedicated YouTube tool for that). Obtain ids from list_videos or search.

  ConnectorNo auth