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Idea nuevaDeveloper tools

"Is it AI?" check API

hace 3 semanas · Evaluada el 23 oct 2026 · ID HBV-261023-09

Título provisional: "Is it AI?" check API and MCP tool for agents before they post, cite or buy (working name)

Resumen

BriefingVerificadoHipótesis

New / agent-services idea (hunch). Benchmark: Imbue Bouncer open models (imbue-ai/bouncer, AGPL-3.0, 403 stars, Verified GitHub API; browser-confirmed on github.com) and commercial detection APIs (Hive, Sightengine). Existence check: Detection APIs exist (Hive, Sightengine, AI or Not, Reality Defender) and Bouncer rele…

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ased open models; no product found positioned specifically as a pay-per-call MCP tool for agents with C2PA + detector + reverse-search in one verdict — the gap is packaging only. X: 211 posts/7d (Up 114% Sat→Thu (full UTC days: Sat 17 14 → Thu 22 30); peak Mon 19 80; Thu 22 is 62% below peak — ≥50% below peak: POP 5.3 window-closed signal; window 2026-10-16 10:05–10:20 UTC (start varies by query) → 2026-10-23 10:00 UTC (X API 7-day limit; Fri 16 and Fri 23 are partial UTC days; full days Sat 17 → Thu 22)). Revenue hypothesis: ~$300–$2K/month at month 6 (HYPOTHESIS).

DescripciónHipótesis

One MCP call returns "likely AI / likely human / unsure" with reasons and C2PA credentials for an image, video frame or text, so agents can avoid reposting, citing or buying AI-made content by mistake. Who: Builders of content, research and shopping agents (indie developers, small agencies) who need a cheap, self-serve check.…

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Pain: Agents repost or cite AI-generated media and buy listings with AI-faked photos; detection APIs are priced and documented for trust-and-safety teams, not for agents. Monetization: Pay-per-call credits (hypothesis ~US$0.002–0.01 per check); free tier via MCP. Build: 1–2 agent-weeks (MCP server, detector ensemble, C2PA read, credits); stack: Vercel functions; open detector models on a GPU host or a wholesale detection API; C2PA library; Stripe credits; MCP server. GTM: MCP directories; GitHub README; GEO.

Cliente objetivo

Builders of content, research and shopping agents (indie developers, small agencies) who need a cheap, self-serve check.

Problema

Agents repost or cite AI-generated media and buy listings with AI-faked photos; detection APIs are priced and documented for trust-and-safety teams, not for agents.

Por qué esta puntuación

Por qué obtuvo una puntuación menor: Commodity detection — margins squeezed by wholesale API costs and open models.

Ventaja defensivaHipótesis

Weak: Ensemble + C2PA packaging is copyable. Only distribution in MCP directories helps. Status: Hypothesis.

Señales de demanda

Publicaciones en X (7 días)

211

Tendencia de la señal

Up 114% Sat→Thu (full UTC days: Sat 17 14 → Thu 22 30); peak Mon 19 80; Thu 22 is 62% below peak — ≥50% below peak: POP 5.3 window-closed signal

Demanda en la webVerificado

X: 211 posts in 7 days, peak Mon 19 (80), Thu 22 is 63% below peak (Verified X API, noisy). Viral demand on the human side is large (see HBV-261023-06), but agent-side demand is not quantified.

Mercado y competidores

TAM

Not sized this run — Scope: AI-content detection APIs. Method: No report fetched. (Basis: n/a)

SAMHipótesis

Not sized — Scope: Agent builders paying per check. Method: HBV assumption. (Basis: Hypothesis)

SOMHipótesis

~$4K–$24K ARR (hypothesis) — Scope: Month-6 run-rate. Method: From revenue hypothesis ×12. (Basis: Hypothesis)

Competidores

Hive AI-generated content detection API; Sightengine; AI or Not API; Reality Defender; Resemble AI (deepfake audio); Imbue Bouncer open models; C2PA verify tools.

Modelo de negocio

MonetizaciónHipótesis

Pay-per-call credits (hypothesis ~US$0.002–0.01 per check); free tier via MCP.

Hipótesis de ingresos (mensual)Hipótesis

~$300–$2K/month at month 6 (HYPOTHESIS).

Jobs to be done

When my agent is about to post or cite an image, I want to check in one call whether it is likely AI, so I can avoid spreading fakes under my brand.

HXC

Indie dev running a news-summary agent (illustrative) · Agent posts daily image roundups on X; got burned by an AI fake. Buying signal: Would add a cheap MCP check; would not sign an enterprise contract.

Construcción y go-to-market

Stack tecnológico

Vercel functions; open detector models on a GPU host or a wholesale detection API; C2PA library; Stripe credits; MCP server

Canales de GTM

MCP directories; GitHub README; GEO

Riesgos

Riesgo principal

Commodity detection — margins squeezed by wholesale API costs and open models.

Todos los riesgos

Value: High — Crowded detection APIs | Usability: Attention — Accuracy limits | Feasibility: Attention — Unquantified agent demand | Business Viability: Attention — GPU cost

Siguiente paso de validación

Do not build now. If HBV-261023-06 (consumer checker) is ever built, expose its backend as an MCP tool at near-zero extra cost.

Fuentes

ideanewagent-servicesai-detectionmcpapideveloper-tools

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La puntuación, las fuentes, los riesgos y el siguiente paso, por correo.

ProductBots.ai

¿Te gusta esta idea? Conviértela en un plan con ProductBots.ai.

ProductBots.ai es un Agentic Product OS: agentes que hacen contigo el trabajo de producto, desde el descubrimiento hasta el plan. Descarga el briefing de esta idea y úsalo como punto de partida.

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# Briefing: "Is it AI?" check API and MCP tool for agents before they post, cite or buy (working name)

Source: Startup Ideas HQ (HB Ventures), found 2026-10-23. ProductBots Opportunity Score: 55/100, evidence confidence 45%.
Evidence labels (Verified, Self-reported, Hypothesis) are kept as written by the researcher.

## Goal for ProductBots.ai
Turn this idea into a validated MVP plan and a first build. Start from the next validation step; do not assume unlabelled numbers are verified.

## What it is
One MCP call returns "likely AI / likely human / unsure" with reasons and C2PA credentials for an image, video frame or text, so agents can avoid reposting, citing or buying AI-made content by mistake.

New / agent-services idea (hunch). Benchmark: Imbue Bouncer open models (imbue-ai/bouncer, AGPL-3.0, 403 stars, Verified GitHub API; browser-confirmed on github.com) and commercial detection APIs (Hive, Sightengine). Existence check: Detection APIs exist (Hive, Sightengine, AI or Not, Reality Defender) and Bouncer released open models; no product found positioned specifically as a pay-per-call MCP tool for agents with C2PA + detector + reverse-search in one verdict — the gap is packaging only. X: 211 posts/7d (Up 114% Sat→Thu (full UTC days: Sat 17 14 → Thu 22 30); peak Mon 19 80; Thu 22 is 62% below peak — ≥50% below peak: POP 5.3 window-closed signal; window 2026-10-16 10:05–10:20 UTC (start varies by query) → 2026-10-23 10:00 UTC (X API 7-day limit; Fri 16 and Fri 23 are partial UTC days; full days Sat 17 → Thu 22)). Revenue hypothesis: ~$300–$2K/month at month 6 (HYPOTHESIS).

## Customer and pain
Target customer: Builders of content, research and shopping agents (indie developers, small agencies) who need a cheap, self-serve check.
Pain: Agents repost or cite AI-generated media and buy listings with AI-faked photos; detection APIs are priced and documented for trust-and-safety teams, not for agents.

## Market and competitors
TAM: Not sized this run — Scope: AI-content detection APIs. Method: No report fetched. (Basis: n/a)
SAM: Not sized — Scope: Agent builders paying per check. Method: HBV assumption. (Basis: Hypothesis)
SOM: ~$4K–$24K ARR (hypothesis) — Scope: Month-6 run-rate. Method: From revenue hypothesis ×12. (Basis: Hypothesis)
Competitors: Hive AI-generated content detection API; Sightengine; AI or Not API; Reality Defender; Resemble AI (deepfake audio); Imbue Bouncer open models; C2PA verify tools.
Geography: Global (English API docs first); Portuguese docs later

## Business model
Monetization: Pay-per-call credits (hypothesis ~US$0.002–0.01 per check); free tier via MCP.
Revenue hypothesis (monthly): ~$300–$2K/month at month 6 (HYPOTHESIS).

## Build and go-to-market
Build effort (agent-weeks): 1–2 agent-weeks (MCP server, detector ensemble, C2PA read, credits)
Time to first revenue: ~1 month
Tech stack: Vercel functions; open detector models on a GPU host or a wholesale detection API; C2PA library; Stripe credits; MCP server
GTM channels: MCP directories; GitHub README; GEO

## Risks and next step
Main risk: Commodity detection — margins squeezed by wholesale API costs and open models.
Next validation action: Do not build now. If HBV-261023-06 (consumer checker) is ever built, expose its backend as an MCP tool at near-zero extra cost.

## Sources
https://github.com/imbue-ai/bouncer; https://thehive.ai; https://sightengine.com; https://www.aiornot.com; https://www.realitydefender.com; X API counts (window above)

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Investigación, no asesoría de inversión. Los números conservan la etiqueta con la que se publicaron.

Resumen

Briefing✓Verificado○Hipótesis

Descripción○Hipótesis