Real Alpha
Server Details
What AI founders and researchers said in long interviews: quotes, speakers, dates and links to cite.
- Status
- Healthy
- Uptime
- 100.0% over the last 24 hours
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- rushabhsheth/realalpha-mcp
- GitHub Stars
- 0
- Server Listing
- Real Alpha MCP server
- ChatGPT
- –
- Claude
- Real Alpha
TDQS
Scored across 7 tools
The seven tools cover search, inspection, episode summary, and transcript roles, but four tools (answers_to, search_moments, latest_moments, what_did_they_say) all retrieve moments with overlapping filters. The detailed descriptions clarify when to prefer each, so boundaries are workable but not fully crisp.
All names use snake_case, but conventions are mixed: get_moment/search_moments/summarize_episode are verb_noun, latest_moments and transcript_excerpt are noun phrases, and answers_to/what_did_they_say are conversational question-like names. They remain readable, but there is no predictable verb_noun pattern across the set.
Seven tools is well within the expected 3-15 range for a focused content-search server, and each maps to a recognizable user need: discovery, detail, episode context, or transcript checking. The set does not feel bloated or thin.
The surface covers the main lifecycle: find moments by query, recency, person, or curated question; inspect a moment; summarize an episode; and verify a quote via transcript excerpt. Minor gaps remain around enumerating all shows/topics/people or retrieving longer transcripts, but core research workflows are covered.
Available Tools
7 toolsanswers_toHow AI leaders answer a big questionARead-onlyIdempotentInspect
How the people building AI answer one of the big questions people ask about it, from the moments Real Alpha cut: grouped by which way they answer, the biggest group first, each with what the speaker says, who they are, the show and date. Use it when someone asks where AI leaders stand on one of these questions; for any other question, search_moments. The questions: is-ai-a-bubble (Is AI a bubble?); which-jobs-will-ai-replace (Which jobs will AI replace, and which are safe?); will-ai-replace-software-engineers (Will AI replace software engineers?); will-ai-replace-doctors (Will AI replace doctors?); will-ai-replace-lawyers (Will AI replace lawyers?); is-saas-dead (Is SaaS dead?); when-will-we-get-agi (When will we get AGI?); is-openai-profitable (How does OpenAI make money, and is it profitable?); ai-predictions (What will AI look like in the next few years?); are-ai-agents-ready (Are AI agents ready for real work?); is-ai-paying-off (Is AI paying off for companies?); is-ai-dangerous (Is AI dangerous?); will-ai-make-cyberattacks-worse (Will AI make cyberattacks worse?); can-anyone-compete-with-nvidia (Can anyone compete with Nvidia?); is-there-a-gpu-shortage (Is there still a GPU shortage?); is-there-enough-power-for-ai (Is there enough power for AI?); is-moores-law-dead (Is Moore’s law dead?); is-ai-progress-slowing (Is AI progress slowing down?); is-open-source-ai-catching-up (Is open-source AI catching up?); is-china-catching-up-in-ai (Is China catching up in AI?); is-ai-overhyped (Is AI overhyped?); will-ai-replace-google-search (Will AI replace Google search?); is-vibe-coding-the-future (Is vibe coding the future?); is-a-computer-science-degree-worth-it (Is a computer science degree still worth it?); are-ai-wrappers-a-real-business (Are AI wrappers a real business?); how-do-ai-companies-make-money (How do AI companies make money?); should-ai-be-regulated (Should AI be regulated?); will-ai-cure-diseases (Will AI cure diseases?); when-will-humanoid-robots-be-useful (When will humanoid robots be useful?); are-self-driving-cars-safe (Are self-driving cars safe?); will-ai-boost-economic-growth (Will AI boost economic growth?); will-ai-replace-accountants (Will AI replace accountants?); will-ai-replace-teachers (Will AI replace teachers?); will-ai-replace-customer-service (Will AI replace customer service jobs?).
Inputs: question (required). Returns: tip, page, groups, question, +1 more
get_momentGet one momentARead-onlyIdempotentInspect
One moment in full, by its slug (from search results) or its realalpha.app/s/ link: the speaker and what they do, the show and date, their quote, the summary and takeaways, its topics, the big questions it answers and how, and the episode's other best minutes. Use it to read a moment closely before quoting it, or when someone shares a realalpha.app/s/ link.
Inputs: slug (required). Returns: url, cite, date, show, +16 more
latest_momentsLatest momentsARead-onlyIdempotentInspect
The newest moments Real Alpha cut, newest episode first: each episode's best minutes, from every show or only one. Use it when someone asks what's new in AI this week from the people building it, what AI leaders have said lately, or what's new on a show.
Inputs: n, show. Returns: moments
search_momentsSearch what AI leaders saidARead-onlyIdempotentInspect
Search the moments Real Alpha cut from long interviews with the people building AI. Use it when someone asks what AI founders, CEOs or researchers have said about a subject, or wants sources, quotes or expert views on an AI question. Matches the words of query against what each moment is about, the speaker's quote and its takeaways, best match first. Filter by who is talking (person), a company (someone from it talking, or it being discussed), a show, or how recent. Each result has the speaker, what they do, the show, the date, their quote, and the moment's page to cite. It only covers the episodes Real Alpha has cut, so no match doesn't mean nobody said it.
Inputs: query (required), show, limit, since, +2 more. Returns: tip, matches, moments
summarize_episodeSummarize a podcast episodeARead-onlyIdempotentInspect
A summary of one long interview or podcast episode Real Alpha cut, found by its YouTube or realalpha.app link, or by words naming it (the show and the guest, or its title): what it covers, the guests and what they do, a point for each part of the conversation with its time, its best minutes in the speaker's own words, the opening of its full analysis, and the page to cite. Use it when someone shares a YouTube link to an AI interview or podcast, or asks to summarize, recap or get the key points of an episode: you can't watch the video, and Real Alpha has listened to it. It covers the episodes Real Alpha cut from the shows it follows; for one it hasn't cut it says so, and how to ask for it.
Inputs: episode (required), show. Returns: cut, dek, tip, url, +18 more
transcript_excerptRead a minute of an episodeARead-onlyIdempotentInspect
About a minute of an episode's transcript, from a second into the video, for an episode Real Alpha cut: the lines with their times and, where the transcript says, who is talking, plus the link that plays the episode from there. Use it to check the exact words around a moment's quote (a moment's episode_url has the video id and second). Only the episodes Real Alpha cut have a transcript, never more than about a minute of one at a time, and a machine transcript can misspell names.
Inputs: video (required), second (required). Returns: url, cite, date, from, +5 more
what_did_they_sayWhat did they say?ARead-onlyIdempotentInspect
What one person said in the interviews Real Alpha cut, newest first: every moment where they are talking, or only those on a topic, best match first. Also says who they are and links their page on Real Alpha, which lists all of it. Use it when someone asks about one named person's views. It only knows people Real Alpha has cut a moment with, and asks for the full name when a name could be more than one person.
Inputs: person (required), limit, topic. Returns: tip, person, moments, on_this_topic, +1 more
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