New startup ideas · AI for people who run the AI themselves · Analysts, researchers and creators running their own stack

startup concept

Mnemos

Your research corpus as a private MCP server every assistant can query

A hosted personal memory for researchers: it ingests notes, PDFs, highlights, interview transcripts and web clips, builds a citable index, and exposes it as a private MCP server.

10

similar startups, last 2 years (20 all-time)

yes

8 matching federal grants and programs

Direction supported by government programs and grants

Test it before you build it

$900 · 4 weeks · 20 prospects

For $900 and 4 weeks, prove that researchers whose libraries outgrew their chat apps will pay for a private corpus endpoint before any indexing code exists.

Riskiest assumption · Researchers with 1,000+ item libraries have already hit the limits of native Claude and ChatGPT file memory and will pay $99 a year for a private cross-assistant endpoint, rather than waiting for the vendors to fix it for free.

1Focus group: who and where

A PhD student, postdoc or independent analyst with a 1,000+ item Zotero or Obsidian library who already pays $20-200 a month for Claude or ChatGPT and this month gave up trying to stuff their references into Projects or file uploads

where to find 20 · Zotero Forums (forums.zotero.org) threads about AI and library size; r/ObsidianMD and r/PhD subreddits; the PulseMCP and Smithery MCP server directories where MCP-curious researchers already browse; a Show HN post of the demo video on Hacker News

2Sell first, build later

A founding slot: your Zotero library and notes folder indexed by hand into a private MCP URL that works in Claude, ChatGPT and Cursor, live within 45 days of your reservation, first year included

the ask · $99 for the first year, reserved with a $49 refundable deposit; planned list price is $15 per month

a real yes · A real yes is a $49 charge on a personal card, or a completed onboarding that is not refunded; forum upvotes, free-waitlist emails and 'I would absolutely use this' comments count for nothing

3Small experiments

The first one attacks the riskiest assumption; each ends with a number that says whether to run the next.

  1. 1. Corpus wall interviews

    $150 · 10 days

    Post a recruiting thread on the Zotero Forums and in r/ObsidianMD asking for researchers with 1,000+ item libraries who use Claude or ChatGPT daily; book 15 twenty-minute calls. On each call, watch how they get sources into an assistant today, ask what broke when they tried Projects or file upload, and end with the $49 reservation link for a $99 founding year.

    keep going if · 10 of 15 have already hit size or citation limits loading their library into Claude Projects or ChatGPT, and 5 of 15 pay the $49 reservation on or within 48 hours of the call

  2. 2. Priced reservation page

    $250 · 14 days

    One-page site with a 90-second screen recording of a hand-built demo (folder of PDFs in, MCP URL out, Claude citing the user's own notes), a $49 refundable reservation checkout, and the $99 founding-year price. Link it from the interview thread, the Show HN post, and coming-soon listings on PulseMCP and Smithery.

    keep going if · 8 reservations from the first 300 unique visitors, a 2.5 percent or better visitor-to-deposit rate

  3. 3. Duct-tape first hour

    $500 · 14 days

    Onboard the first 5 depositors by hand: index their exported library with off-the-shelf open-source retrieval plus the MCP SDK, no product code, and get each a working private MCP URL inside one call. Track their query counts for two weeks.

    keep going if · 4 of 5 ask 10 or more questions against their corpus in the second week and none request a refund

4Collect a deposit up front

Tesla took $1,000 refundable reservations for the Model 3 and $100 for the Cybertruck before building either: the deposit is the measurement, not the revenue.

$49

per prospect, refundable

how · A refundable $49 reservation through a hosted card checkout linked from the landing page and dropped in chat at the end of each interview; this buyer is a consumer paying with a personal card, so a one-click checkout is the only rail that closes on the call, and no LOI or invoice fits set up: Stripe Invoicing

what it reserves · A slot in the 10-person founding cohort, the $99 first-year price locked, and hand onboarding of their specific library within 45 days

refund · Refunded in full within 5 business days on request any time before onboarding, or automatically if their MCP URL is not live within 45 days

target · 10 reservations from 15 calls plus 300 landing visitors within 28 days

Go: build it if

10 paid $49 reservations in 4 weeks, and 4 of the first 5 onboarded users querying their corpus 10+ times in week two with zero refunds

Kill: stop if

Fewer than 4 reservations after 15 calls and 300 visitors, or 10+ of 15 interviewees say Claude Projects or ChatGPT memory already handles their library fine

5 Scripts to run itoutreach message, landing copy, deposit terms · click to open

outreach message

Saw your post about your reference library outgrowing what Claude can hold. I'm building Mnemos: upload your PDFs and notes export, get a private MCP URL, and Claude, ChatGPT or Cursor answers from your own corpus with source pointers. Before I write real code I'm doing 15 setup walkthroughs with researchers running 1,000+ item libraries. Could I get 20 minutes with you this week? Either way I'll send you notes on how I'd index your setup.

landing page

Your research library, answering inside every assistant you use $49 refundable reservation locks a founding slot and your first year at $99 Reserve your private MCP endpoint

deposit terms

Your $49 reserves one of 10 founding slots and locks your first year at $99 instead of $180. We index your library by hand and your private MCP URL goes live within 45 days of checkout. Change your mind before onboarding, or miss our 45-day deadline, and the full $49 is refunded within 5 business days.

Would you run this test?

One tap. The yes-share feeds the Demand pillar of this idea's score; nobody sees who answered.

Budgets are out-of-pocket estimates for a team of one to three, US market. Size the deposit to the deal, and check the terms before taking money in a regulated line.

Scorecard

Ranked against every idea in the catalog: trend, demand and 100x potential from the corpus, competition relative to the other ideas. A generated concept has no judges or swipes yet, so its pillars use the data signals only.

34

Idea Score, 0-100 · raw 21.0 x 1.61

Crowded

competition: more crowded than 78% of ideas · headwind x0.61

+4.6

government priorities, secondary (92 matching grants)

Trend

47

Is the wave forming now? 2025-26 entrants vs 2023-24, rounds since 2025, the sector's live-batch direction, the 2026 trend analyst.

  • Entrants 2025-26 vs 2023-24 (similar companies)90
  • Rounds announced 2025+ in the sector0
  • Sector direction (live batch)50

Demand

65

Does anyone want it? YC's current RFS, companies already paid for something similar, the operator judge, founders' yes-rate in decks, readers who would run the test.

  • YC asks for it (current RFS: idea / sector)30
  • Someone already pays (similar companies, recent / all-time)100

100x potential

6

Can it return a fund? The venture judge (double weight), market-size and moat axes, neighbours still alive, the technologist judge.

  • Neighbours still alive6

Score = 100 x cbrt(Trend x Demand x 100x) x (1 - 0.5 x crowding) + government bonus (max 5), calibrated so the 95th-percentile idea scores 90 (order never changes). A geometric mean: a weak pillar cannot be papered over. Percentiles are among the 382 ideas in the catalog; the terms matched were research, corpus, private, mcp, server, assistant, hosted, personal.

The concept in full

What
A hosted personal memory for researchers: it ingests notes, PDFs, highlights, interview transcripts and web clips, builds a citable index, and exposes it as a private MCP server. Claude, ChatGPT, Cursor or any MCP client then answers from the user's own corpus with source pointers. In the first hour a user uploads a folder of PDFs and their notes export, gets an MCP URL, plugs it into Claude, and asks a question only their corpus can answer.
Grounded in (2025-2026 signals)
On December 9, 2025 Anthropic donated MCP to the Agentic AI Foundation under the Linux Foundation, with 97 million monthly SDK downloads, 10,000 active servers, and first-class support in ChatGPT, Claude, Cursor, Gemini, Copilot and VS Code. Alpha Research (yc X25, 2025, alive) builds 'open source, agentic knowledge bases for all of humanity's knowledge', signaling the agentic knowledge base pattern, but aimed at public knowledge rather than one person's corpus.
What it rides
Rides 'MCP donated to the Agentic AI Foundation': one plug any user's assistant can take means a personal corpus no longer has to live inside one vendor's app; it can be infrastructure the person owns and points every tool at.
Why now
MCP hit 97 million monthly SDK downloads and 10,000 active servers as of the December 9, 2025 foundation announcement, so for the first time a single private endpoint reaches every major assistant a researcher already uses; a year ago this required per-app plugins that did not exist.
Wedge: first customer and entry point
Academics and independent analysts on $100-$200-a-month Max or Pro plans whose reference libraries outgrew any one chat app; the entry point is 'connect your Zotero or PDF folder, get your MCP URL in ten minutes.'
Closest real companies, as the generator saw them
Alpha Research builds agentic knowledge bases for humanity's public knowledge; Mnemos is one person's private corpus with their annotations. ZeroEntropy works on specialized retrieval as developer infrastructure; Mnemos is a finished self-serve product for a non-developer researcher.
Main risk
Claude and ChatGPT ship good-enough native memory over uploaded files, and only users with unusually large or cross-tool corpora still pay.

Similar startups in the directory

Companies whose pitch matches most of the concept's terms (research, corpus, private, mcp, server, assistant, hosted, personal).

  • Egoist Machinesyc S26 · 2026 · Agent infrastructurealive

    Your personal context, securely portable across every AI app.

  • Moonshotyc S26 · 2026 · Consumeralive

    agents for the rest of us

  • Palma.aiplugandplay PnP 2026 · 2026alive

    One connector per employee. Every AI tool and skill your company allows, and nothing else.

  • Scopeyc X26 · 2026 · Developer toolsalive

    We help software companies get discovered and used by AI agents

  • Pavootyc X26 · 2026 · B2B SaaSalive

    AI Event Manager for in-person events

  • Soriayc X26 · 2026 · Fintechalive

    AI Financial Research Terminal built for Healthcare (and beyond)

  • E1Oyc X26 · 2026 · Consumeralive

    Camera-free AI glasses. Your AI, out in the world.

  • AirCapsyc F25 · 2025 · Horizontal AI assistantsalive

    The AI copilot for in-person conversations.

  • Havilo.aialchemist Alchemist Class 40 · 2025 · Vertical AI agentsunchecked

    The intelligence layer for the world's most valuable networks.

  • Epicenteryc S25 · 2025 · Horizontal AI assistantsalive

    ChatGPT's memory feature in an open, portable format

  • Comfy Deployyc S24 · 2024 · Developer toolsalive

    ComfyUI for everyone on your team

  • Magic Houryc W24 · 2024 · Developer toolsalive

    AI media creation platform for creators and developers

Public money in this direction

US federal grants and open opportunities matched to the concept's terms.

Other concepts in this collection

Fictional concept generated 2026-08-26 by claude-fable-5 from the collection's brief and MarkosWeb data. Treat it as a research prompt, not a plan.