"Information about theHarvester tool" matching MCP connectors:
GET /v1/connectors – MCP directory API referenceMatching Connector Tools:
formcarry handles everything after your form is submitted: it emails you, auto replies to the person who submitted, filters spam, and delivers webhooks. You write the HTML form and set its action to a URL formcarry gives you. An agent can create a form, wire the emails and webhooks, and answer questions about the submissions, like how many signups last week.
Server-side conversion tracking for Meta, TikTok, etc. Set up tracking and ask about events.
Read-only access to your own crypto portfolio across 11+ exchanges and 20+ chains: holdings, full history, FIFO cost basis and P&L, fees and income. Ask Claude or ChatGPT about your portfolio; the connector can never trade, move funds or act as a login.
Control your existing Philips lights, Sonos speakers, Roborock vacuums and other supported devices through Port OS cloud. Give ChatGPT, Claude and other MCP-compatible assistants access to the devices you connect. Turn off the living room lights, play music on your speakers, adjust the thermostat, run a vacuum in a room, check a camera snapshot or find a connected tracker. Available actions depend on your linked provider accounts and each device’s supported capabilities. Port OS runs in the cloud; no local server is required. You choose the account, device and capability permissions each assistant receives. Device operations require user OAuth; public tool discovery does not grant device access. Port OS is in alpha. Setup: https://portoperatingsystem.com/docs/getting-started/ Support: https://portoperatingsystem.com/contact/
Marcora is the context layer for go-to-market teams. Build your source of truth once: a Brand Foundation (positioning, brand voice, and writing style) plus a Reference Library of product docs, buyer personas, competitive analysis, and messaging. Claude, ChatGPT, and any AI tool that supports MCP connections read from it, so what you write stays on-brand and accurate.
Keep your household on the same page with ComingUp Today. Built for families and caregivers managing busy schedules, ComingUp brings calendars, lists, notes, contacts, and recipes together. Connect your AI assistant to see what’s coming up, add groceries, find household information, save recipes, and create or update ComingUp events—all through conversation. Connect securely with OAuth and choose the permissions you grant. Connected external calendars remain read-only.
Read-only: transactions, budgets, forecasts and insights from the PocketSmith personal finance tool.
The only News based AI MCP your agents will ever need — custom categories, global regions, and time-scoped results in one tool. We use multi-vector & sparse-hybrid search to search through thousands of articles across the world to find the exact news you're looking for.
Explore your user test data, summarize feedback, and uncover actionable insights faster. Ask questions about tests, participants, tasks, and findings in plain language.
Runtime permission, approval, and audit layer for AI agent tool execution.
XMemo is a user-owned Memory OS for AI agents, providing a shared, persistent memory layer across AI assistants, IDEs, CLIs, tools, projects, and sessions. It enables ChatGPT, Claude, Codex, Cursor, Gemini, and other supported AI clients to access authorized long-term context without requiring users to repeatedly explain their preferences, project decisions, or previous work. Beyond basic memory storage and retrieval, XMemo supports semantic search, contextual recall, memory updates and corrections, source attribution, version history, project-scoped context, task tracking, and governed memory lifecycle management. Identity-aware access controls, scoped authorization, and memory isolation help users manage which agents and workflows can access their information. XMemo also provides advanced capabilities for structured knowledge, reusable procedures, and memory consolidation through its broader Memory OS platform. Connect through hosted MCP with OAuth or bearer-token authentication, or integrate directly through REST APIs and supported client tools. Memory remains available across authorized clients and sessions, with user-controlled access, export, and deletion. Website: https://xmemo.dev Documentation: https://xmemo.dev/docs
Work with transactions, budgets, forecasts and insights from the PocketSmith personal finance tool.
Connect your Odoo to Claude and ChatGPT: ask about sales, stock, customers and invoices.
Research U.S. markets and prospects conversationally using PropertyRadar's property and people data. Resolve an address, inspect Property details, transactions, comparable sales, ownership and contact information, discover supported Criteria and fields, search for matching Properties, and save selected results as a dynamic Audience. PropertyRadar accesses only the data available to your connected account.
Levelset puts StandPoint's market research desk inside your assistant. Ask about a stock the way you would ask a person, and the answer comes back with real numbers from the desk's data instead of a guess.
ASOClimb brings App Store Optimization into your AI assistant. Connect it once with OAuth sign-in, then ask in plain language about the apps you publish on the Apple App Store and Google Play. What it can do: - Keyword research: live keyword inspections with traffic, difficulty and KEI scores, top-ranking apps and related terms, plus live store autocomplete suggestions. - Rank tracking: track keywords for your apps, see daily rank observations, movers, favorites and rank alerts. - Competitors: track competitor apps, see the keywords they rank for, and find keyword gaps where they rank and you don't. - Market research: top free, paid and grossing charts, new releases, category ranks and niche analysis from a seed keyword. - Listing copy: check any App Store or Google Play listing, simulate new titles, subtitles and keyword fields against store character limits, save drafts and compare them with the live listing. - Account: see your plan, limits and month-to-date usage. Ranks are dated observations, not store-provided data. Tools that only read data are marked read-only. Only two tools remove data: untrack_keyword and remove_competitor. Plans: Free costs $0, covers 1 app, and includes 25 keyword inspections and 500 API/MCP requests a month. Pro costs $10 a month or $100 a year, covers up to 50 apps, includes unlimited keyword inspections and 50,000 API/MCP requests a month, and is sold at asoclimb.com/pricing. Monthly allowances reset on the 1st (UTC). Built by Approtic Solutions Private Limited.
Connect compatible AI assistants to your own registered and authorized Windows or macOS computers for file operations, terminal commands and device management. Free: 1 device, 10,000 MCP tool calls per month; allowance resets next month.
Run accessibility, contrast, and design token audits and file QA issues from your AI coding tool.
Ask Claude or ChatGPT about your own finances. ValYou gives read-only answers on your net worth across every account and currency, what moved since last month, where you rank for your age, retirement projections, what-if scenarios, shared expenses with friends and your monthly budget. Nothing is changed and no account numbers are ever shared.
Connect Chatway, an AI-powered website live chat and customer support platform, to ChatGPT, Claude, Gemini, Cursor, and other AI assistants using MCP. Chatway helps businesses communicate with website visitors, manage customer conversations, and deliver faster support across multiple channels, including website live chat, email, WhatsApp, Instagram, and Facebook Messenger. Native mobile apps for iOS and Android let support teams manage conversations and respond to customers on the go. With Chatway's MCP server, AI agents can access and manage customer support operations. Search and read conversations, send replies, add private notes, resolve and assign chats, manage contacts, retrieve customer information, and search knowledge base articles. Chatway also includes a built-in AI Support Agent for automated customer service, a shared team inbox, support ticket management, a customizable website chat widget, a help center, team management, automated workflows, visitor tracking, and integrations with popular platforms, including WordPress and Shopify. Connect external AI agents to automate customer support, answer customer questions, access conversation history, and streamline support workflows without building custom integrations. Manage your customer support from anywhere using Chatway's web dashboard or mobile apps. The hosted MCP server supports Streamable HTTP and secure OAuth 2.1 authentication with scoped permissions. Available on all Chatway plans, including the Free plan. Conversation limits apply. Website: https://chatway.app Documentation: https://developers.chatway.app/mcp/guides.mcp_overview
LastDatabase is an OAuth-enabled MCP server providing AI assistants with access to B2B and B2C lead data. Discover business contacts, search companies and professionals, access available contact information, and verify email addresses through supported tools. Integrates with ChatGPT, Claude, and other MCP-compatible AI clients. Customer authentication, data access, and usage limits are managed through individual LastDatabase accounts.
Vigilia watches your live app, explains every problem in plain language and writes the fix prompt. Your AI fixes it; Vigilia confirms with real traffic. Vigilia watches web apps that are live with real users, including apps built with Lovable, Bolt, v0, Cursor and Claude Code. It catches errors, failed requests and downtime, explains each problem in plain language, and writes a fix prompt for it. Connect Vigilia to Claude and ask what's broken. Claude lists your open incidents worst first. For each one it reads the plain-language diagnosis, who it affects, the technical evidence (error, page, failing request, stack frames and what the visitor did right before) and Vigilia's fix prompt. In Claude Code or another coding agent, Claude can then fix the cause in your own codebase. Once you've deployed, it marks the incident fixed, and Vigilia watches real traffic to confirm the error stayed away. If it comes back, the incident reopens as a regression. You can also ask how an app is doing (uptime, open incidents, today's traffic), get the exact install snippet for a new project, and check that a live site is running Vigilia. Vigilia never reads or changes your code: the fixing happens in your session, by your AI, in front of you. The only tool that changes anything is marking an incident fixed (the install check just records its result on the app), and you can connect with read-only access. Your data is stored in the EU. Emails, tokens and card numbers are stripped from what visitors' browsers send, and only that scrubbed error context is sent to Anthropic to write the diagnosis. Requires a Vigilia account. The free plan covers one app; reporting backend errors (Supabase, Next.js routes, Workers) is part of Pro.
What people who use a piece of software say about it: vouches, recommends and their reasons.
Connects your PapaHR HR system to AI assistants. Ask about employees, time off, probation endings, hiring, surveys and eNPS, goals, pending approvals, and what turnover costs. OAuth sign-in; the AI connection is part of PapaHR Pro.
Create a beacon: a few plain words about what you have or need. Any agent can find and message it.
# **RChilli** RChilli MCP Hub is a production-grade Model Context Protocol (MCP) server that exposes RChilli’s HR data intelligence platform through AI-callable tools. Built on 15+ years of HR data intelligence, RChilli supports ATS vendors, HR technology platforms, staffing agencies, and enterprise recruiting teams worldwide. The tools return consistent, structured JSON responses for recruiting, talent intelligence, skills, matching, compliance, and HR workflow use cases. `userkey` and `subuserid` are injected automatically from the Bearer token and must not be passed manually. <br> --- <br> # **Available Tools** <br> > ### **`analyze_hr_call`** > > Transcribes and analyzes HR or recruiting call recordings to extract speaker turns, sentiment, candidate intent, action items, skill mentions, and structured follow-up data for recruiting operations. <br> > ### **`analyze_skill_adjacency`** > > Identifies related, adjacent, and transferable skills to support skill discovery, talent mobility, workforce planning, and candidate evaluation. <br> > ### **`analyze_skill_gap`** > > Compares candidate or employee skills against a target job and returns present skills, missing skills, readiness score, and development areas for hiring, internal mobility, and workforce planning. <br> > ### **`autocomplete_job_profile`** > > Accepts a partial job title and returns ranked autocomplete suggestions with canonical titles and job families. Ensures job titles map to standardized taxonomy profiles from the moment a recruiter starts typing. <br> > ### **`autocomplete_skill`** > > Accepts a partial skill string and returns ranked autocomplete suggestions with canonical skill names and categories. Helps prevent free-text entry errors and keeps skill data clean. <br> > ### **`classify_job_zone`** > > Reads the job profile from a resume or job description and returns its O*NET Job Zone, from Zone 1 through Zone 5, based on the education, experience, and training preparation required for the role. <br> > ### **`convert_document_format`** > > Accepts a document as base64 or URL and converts between PDF, DOCX, RTF, HTML, and plain text. Useful as a pre-processing step before extracting data from non-standard document formats. <br> > ### **`detect_bias`** > > Reviews job descriptions and hiring criteria for gendered language, age-coded terms, unnecessary credential inflation, cultural exclusion signals, and related compliance risks. Suggests neutral replacements. <br> > ### **`detect_resume_suspicion`** > > Reviews candidate profile data for possible inconsistencies, unusual claims, timeline conflicts, missing context, and other signals that require recruiter review. <br> > ### **`extract_contacts`** > > Identifies and structures names, emails, phone numbers, LinkedIn URLs, and addresses with field-level confidence scores from candidate records, emails, or documents. <br> > ### **`extract_job_data`** > > Extracts and converts job descriptions into structured hiring data including job title, required skills, preferred skills, responsibilities, experience, education, and taxonomy-normalized role requirements. <br> > ### **`extract_resume_data`** > > Extracts and converts resumes, CVs, and candidate documents into structured, searchable profiles with contact details, skills, experience, education, certifications, and taxonomy-enriched data for ATS, HCM, and AI recruiting workflows. Supports multilingual extraction, batch processing, resume auto-fill, and reprocessing of historical resumes. <br> > ### **`extract_resume_data_from_url`** > > Accepts a direct URL to a PDF, DOCX, or RTF file and returns the same normalized JSON profile as Resume Data Extraction. Ideal for resumes stored in cloud storage, S3, email attachments, or other URL-accessible sources. <br> > ### **`find_matches_in_index`** > > Accepts a resume or job description as input and returns the top matching documents from the indexed corpus, ranked by semantic similarity. <br> > ### **`generate_interview_questions`** > > Creates technical, behavioral, situational, and competency-based interview questions tailored to a role and candidate profile, including question type, competency, and expected answer signals. <br> > ### **`generate_jd`** > > Generates structured job descriptions with title, responsibilities, required skills, preferred skills, qualifications, tone alignment, language support, and inclusivity scoring from role inputs. <br> > ### **`geolocate`** > > Converts partial or informal location text into structured city, state, country, ISO codes, latitude, and longitude. Supports radius-based candidate search and workforce planning. <br> > ### **`index_document`** > > Indexes a resume or job description in RChilli Search & Match so it can be searched, matched, updated, and reused across candidate matching, job matching, and similarity-search workflows. <br> > ### **`lookup_job_profile`** > > Returns authoritative detail for a known job profile including canonical title, SOC/O*NET code, job family, typical required and preferred skills, salary bands, and work context. <br> > ### **`lookup_skill`** > > Returns authoritative detail for a known skill including description, aliases, related skills, proficiency levels, and O*NET or ESCO mappings. <br> > ### **`map_job_to_skills`** > > Converts job descriptions into granular skill maps with required and preferred skill clusters, proficiency signals, taxonomy tags, and downstream matching attributes. <br> > ### **`match_end_to_end`** > > Orchestrates data extraction, indexing, taxonomy normalization, and matching to return ranked candidates or jobs with scores, explainable results, and an audit trail from a single call. <br> > ### **`normalize_candidate_data`** > > Cleans and normalizes candidate records from multiple ATS or HR systems, resolves field conflicts, deduplicates records, and produces standardized candidate data with a field-level change log. <br> > ### **`normalize_hr_data_with_lov`** > > Maps raw and inconsistent HR data values, including degrees, universities, certifications, job profiles, skills, and locations, to the closest configured List of Values entry with a standardized value and confidence score. <br> > ### **`recommend_learning_path`** > > Builds structured learning paths with prerequisites, skill sequence, certifications, proficiency targets, and LMS alignment based on a person’s profile and target role. <br> > ### **`redact_resume`** > > Redacts configured personally identifiable information from candidate profiles to support anonymized review, bias-aware screening, compliance workflows, and audit logs. <br> > ### **`reformat_resume_with_template`** > > Applies one of the RChilli resume templates, TM001 through TM006, to a structured candidate profile and produces a consistently formatted PDF, DOCX, RTF, or HTML document. <br> > ### **`score_resume_against_jd`** > > Accepts one resume and one job description and returns an overall match score, dimension scores, matched skills, skill gaps, and a natural-language explanation. No index is required. <br> > ### **`screen_application_batch`** > > Evaluates a batch of candidates against job requirements and custom criteria, returning scores, insights, skill gaps, and recommended next actions for each candidate. <br> > ### **`search_indexed_documents`** > > Accepts a query string and returns ranked document references from the tenant’s indexed corpus. Supports Boolean and semantic search modes. <br> > ### **`skill_mapping`** > > Maps raw skill text to standardized RChilli taxonomy skills, aliases, classifications, and related skill information. <br> > ### **`tag_entities`** > > Annotates extracted HR text by wrapping recognized entities in structured XML-style labels. Supported entities include job titles, skills, names, degrees, organizations, locations, countries, dates, and years.
Search about 10 million U.S. court decisions, every state's statutes and the official rules for 3,400 courts, from your AI app. Free account: 40 lookups a day. Legal Ops Depot's law library as a remote MCP connector. Search case law, read full opinions, follow 77.5 million citation links, look up statutes and court rules, and check that a citation exists, with the cases that bind your court ranked first. Works in Claude, Grok and other MCP clients. Not legal advice. Homepage: https://www.legalop
# Poof **Poof ([poof.bg](https://poof.bg)): a background removal API for AI agents. Send an image, get the subject back on a transparent background in under 2 seconds.** [Poof](https://poof.bg) gives your assistant a background removal tool. It handles people, products, cars, animals, and graphics, with hair-level edge precision, and returns a transparent PNG or WebP, or a solid-colour JPG for product listings. Pricing starts at $0.002 per image, with 100 free credits every month. This repository is the integration front door. The product itself lives at [poof.bg](https://poof.bg); the remote MCP server lives at `https://api.poof.bg/mcp`. ## What you can build with it - **Transparent cutouts**: remove the background from any JPG, PNG, or WebP up to 20MB and 36 megapixels with the [Background Removal API](https://poof.bg/background-removal-api). - **E-commerce product photos**: white or brand-colour backgrounds, cropped to the subject and resized to a fixed canvas, so every listing image matches. - **A remove.bg replacement**: remove.bg shuts down on 1 December 2026. Poof accepts the same inputs, so most integrations only change the endpoint and key. See the [remove.bg alternative and migration guide](https://poof.bg/alternative/remove-bg). - **Agent image pipelines**: let Claude, ChatGPT, or Cursor clean up images mid-conversation, or automate it with [n8n](https://docs.poof.bg/integrations/n8n), [Zapier](https://docs.poof.bg/integrations/zapier), and [Make](https://docs.poof.bg/integrations/make). ## Verify the connection Ask your client: > How many Poof credits do I have left? You should see a `get_account` tool call and your real plan and balance. Then try: > Remove the background from https://example.com/product.jpg and give me a white background JPG. ## What the tools do The server exposes 2 tools. - **`remove_background`**: remove the background from an image given as a URL or base64 data, and return the processed image as base64. Optional parameters control the result: - `format`: `png` (default), `jpg`, or `webp`. - `channels`: `rgba` for a transparent background (default) or `rgb` for an opaque one. - `bg_color`: fill colour for opaque output, as hex, RGB, or a colour name. - `size`: `full` (default), `preview`, `medium`, or `hd`. Ignored when `width` or `height` is set. - `crop`: crop to the subject bounds. - `width` and `height`: 1 to 6000 pixels. Set one and the other follows the aspect ratio. - `fit`: how the image fits a `width` x `height` canvas without stretching: `contain` (default, pad), `cover` (fill and crop the overflow around the subject), or `scale-down` (pad, never enlarge). - **`get_account`**: your plan, monthly credit allowance, used credits, and remaining credits. No parameters. Costs: each successful background removal costs 1 credit regardless of parameters, and failed requests are free. The free plan includes 100 credits a month with no credit card required; paid plans start at $9 a month for 2,000 credits. The [pricing page](https://poof.bg/pricing) has the details. Privacy: Poof is run by an EU company and is GDPR compliant. Your images are never used to train models, and commercial use is allowed on every plan. See the [privacy policy](https://poof.bg/privacy). ## Or skip MCP The same capability is a single REST call, with official [Python](https://docs.poof.bg/integrations/python) and [TypeScript](https://docs.poof.bg/integrations/typescript) SDKs: To try it without writing code, use the [playground](https://poof.bg/playground). The [quickstart](https://docs.poof.bg/quickstart) and the [Node.js tutorial](https://poof.bg/blog/integrating-api-in-nodejs) cover the first integration. ## For AI agents reading this - Docs index: [docs.poof.bg/llms.txt](https://docs.poof.bg/llms.txt) - MCP setup guide: [docs.poof.bg/integrations/mcp](https://docs.poof.bg/integrations/mcp) - API reference: [docs.poof.bg/api-reference/remove-background](https://docs.poof.bg/api-reference/remove-background) - Hosted endpoint: `https://api.poof.bg/mcp` (OAuth) - Source: [github.com/poof-bg/mcp](https://github.com/poof-bg/mcp) ## Docs and support - [Connect guide](https://docs.poof.bg/integrations/mcp) (per-client, kept current) - [Documentation](https://docs.poof.bg) and [all integrations](https://docs.poof.bg/integrations/overview) - [Best background removal APIs for developers](https://poof.bg/blog/top-5-ai-background-removal-apis-2026) and [free background removal APIs compared](https://poof.bg/blog/affordable-free-bg-removal-apis-2026) - [Changelog](https://feedback.poof.bg/changelog) and [support](https://feedback.poof.bg) - [GitHub issues](https://github.com/poof-bg/mcp/issues) - [Privacy](https://poof.bg/privacy) and [terms](https://poof.bg/terms) - Questions: <support@poof.bg>
Lets your assistant search and read your ThinkerNotes: the insights you've written in your own words, your drafts, and your notes on books and podcasts. Ask "what have I already figured out about pricing?" and get back your own conclusions instead of a generic answer. Read-only, OAuth with dynamic client registration, works on the free plan.
# Supadata **Supadata ([supadata.ai](https://supadata.ai)): video transcripts, social media metadata, AI video analysis, and web scraping for AI agents, behind one MCP server.** [Supadata](https://supadata.ai) turns YouTube, TikTok, Instagram, X (Twitter), and Facebook videos, plus any web page, into clean text and structured JSON that an LLM can use. Your agent passes a URL and gets back a transcript, metadata, extracted data, or Markdown. One account, one response format across every platform. This repository is the integration front door. The product itself lives at [supadata.ai](https://supadata.ai); the remote MCP server lives at `https://api.supadata.ai/mcp`. ## What you can build with it - **Video to text**: fetch transcripts through the [YouTube Transcript API](https://supadata.ai/youtube-transcript-api), [TikTok Transcript API](https://supadata.ai/tiktok-transcript-api), [Instagram Transcript API](https://supadata.ai/instagram-transcript-api), and [X (Twitter) Transcript API](https://supadata.ai/twitter-transcript-api). When a video has no captions, the [AI Transcription API](https://supadata.ai/video-transcript-api) generates one, and it works on direct video file URLs too. - **Video and channel metadata**: titles, descriptions, authors, views, likes, and comments as clean JSON, a simpler [YouTube Data API alternative](https://supadata.ai/youtube-api) that also covers TikTok, Instagram, X, and Facebook. - **Structured data from video**: give a prompt or a JSON schema and the [Video Analysis API](https://supadata.ai/video-analysis-api) returns structured output that accounts for visuals, audio, and context. - **Web context**: scrape any page to Markdown, map a site's URLs, or crawl a whole site for RAG and research. See the [web scraping docs](https://docs.supadata.ai). ## Verify the connection Ask your client: > Get the transcript of https://www.youtube.com/watch?v=dQw4w9WgXcQ and summarize it in three bullet points. You should see a `supadata_transcript` tool call and a real summary. ## What the tools do The server exposes 9 tools in four groups. - **Transcripts**: `supadata_transcript` (get a transcript from a YouTube, TikTok, Instagram, X, or Facebook video URL, or from a direct file URL; uses existing captions when available and falls back to AI transcription when there are none), `supadata_check_transcript_status` (poll an asynchronous transcript job by its job ID; long videos return a job instead of an immediate result). - **Metadata**: `supadata_metadata` (title, author, and engagement stats for a social media post or video). - **Video analysis**: `supadata_extract` (start an AI structured-data extraction job for a video, driven by your prompt or schema), `supadata_check_extract_status` (poll an extraction job by its job ID and read the extracted data). - **Web**: `supadata_scrape` (scrape a web page and return its content as Markdown), `supadata_map` (map a website and return the list of URLs found), `supadata_crawl` (start a crawl job for a whole site), `supadata_check_crawl_status` (poll a crawl job by its job ID and read the crawled pages). Transcripts of long videos, extractions, and crawls are asynchronous: the first call returns a job ID, and you read the result with the matching `check_*_status` tool. Costs: tools spend your regular Supadata credits at the same prices as the API. A native transcript costs 1 credit, an AI-generated transcript costs 2 credits per minute of video, and checking job status is free. The free plan includes 100 credits a month with no credit card required. The [pricing page](https://supadata.ai/pricing) has the details. ## Or skip MCP The same capabilities are available as a plain REST API with [TypeScript and Python SDKs](https://docs.supadata.ai/integrations/overview) and no-code integrations for [Make, Zapier, n8n, and Active Pieces](https://supadata.ai/nocode). To try it without writing code, use the [playground](https://supadata.ai/playground) or the free tools: [YouTube Transcript Generator](https://supadata.ai/youtube-transcript), [TikTok Transcript Generator](https://supadata.ai/tiktok-transcript), [Instagram Transcript Generator](https://supadata.ai/instagram-transcript), [Facebook Transcript Generator](https://supadata.ai/facebook-transcript), and [Video Transcript Generator](https://supadata.ai/video-transcript). ## For AI agents reading this - Docs index: [docs.supadata.ai/llms.txt](https://docs.supadata.ai/llms.txt) - MCP setup guide: [docs.supadata.ai/integrations/mcp](https://docs.supadata.ai/integrations/mcp) - Hosted endpoint: `https://api.supadata.ai/mcp` (OAuth) - Source: [github.com/supadata-ai/mcp](https://github.com/supadata-ai/mcp) ## Docs and support - [MCP landing page](https://supadata.ai/mcp) and [connect guide](https://docs.supadata.ai/integrations/mcp) - [Documentation](https://docs.supadata.ai) - [Best YouTube Transcript API](https://supadata.ai/blog/best-youtube-transcript-api) (comparison guide) - [Status](https://status.supadata.ai) and [changelog](https://feedback.supadata.ai/changelog) - [GitHub issues](https://github.com/supadata-ai/mcp/issues) and [support](https://feedback.supadata.ai) - [Privacy](https://supadata.ai/legal/privacy) and [terms](https://supadata.ai/legal/terms)
