Round 1 Winners!
Proof of Usefulness Report

Job Verify: Detect fake recruiter & job-offer scams with free

Analysis completed on 7/4/2026

+64
Proof of Usefulness Score
You're In Business

JobVerify presents a highly relevant and innovative use of the Model Context Protocol (MCP) to tackle the rising problem of job and recruiter scams. While the project is in its infancy with minimal traction (118 PyPI downloads, 5 GitHub stars), the problem-solution fit is exceptionally strong. The clear, thoughtful submission highlights a privacy-first, free-to-use OSINT integration that perfectly aligns with current AI assistant capabilities. Scalability and audience reach will dictate future score growth.

View All Reports

Score Breakdown

Real World Utility+22.50
Audience Reach Impact+4.00
Technical Innovation+12.00
Evidence Of Traction+6.25
Market Timing Relevance+9.50
Functional Completeness+7.13
Subtotal+61.38
Usefulness Multiplierx1.05
Final Score+64

Project Details

Description
JobVerify helps you find out — in seconds — whether it's genuine or a scam. You paste the recruiter's message (or a company name, a link, or an email) and ask your AI assistant. JobVerify quietly runs the same background checks a professional investigator would, then gives you a answer: looks legit, be careful, or this is almost certainly a scam — and why.
Audience Reach
JobVerify is an MCP server that checks whether a recruiter or job offer is genuine before you respond. Paste a message, company, link, or email — it runs the same background checks a fraud investigator would, using only free public OSINT (no API keys, nothing stored), and returns a plain-English verdict: looks legit, be careful, or almost certainly a scam — and why.
Target Users
Who's It For Job seekers — especially anyone applying to remote roles, where fake "we loved your profile" offers are everywhere. Check a recruiter before you reply, share personal info, or send money. New grads & career switchers — the people scammers target most, with "onboarding equipment" fees and fake task jobs. Freelancers & contractors — who get cold offers from unknown "clients" and need to vet them fast. Recruiters & HR teams — to spot imposters using their company's name and protect candidates from brand-impersonation scams. Security & OSINT folks — anyone who wants an automated, no-API-key way to run the standard verification checklist on a suspicious message. If you've ever stared at a job offer thinking "this looks real… but something feels off," JobVerify is for you.
Technologies
Other
Traction Evidence
Evidence of Traction JobVerify is early-stage but already shipped and usable today: - Live and installable: published on PyPI (`uvx jobverify-mcp`) and listed in the Model Context Protocol registry, so anyone can run it in Claude with a single line — no setup, no API keys. - Open source (MIT) on GitHub, with 20+ working OSINT tools and a one-command `analyze` flow already implemented. - Built in response to a real problem: created after a live fake-recruiter scam attempt — the exact use case it solves. - Zero-cost to run and privacy-first (no sign-up, no data stored), removing the usual adoption barriers. - Growing distribution: submitted to the major MCP directories (Smithery, Glama, mcp.so, PulseMCP, awesome-mcp-servers) where MCP users actively discover new servers. Early numbers (first days after launch): - 118 PyPI downloads in the first week — from a standing start, with the package barely a day old. - Published and live on PyPI (jobverify-mcp v0.1.0) and the MCP registry. - 5 GitHub stars and a fork within 24 hours of the repo going public. - 20+ OSINT verification tools shipped and working, all free / no API keys.

Algorithm Insights

Market Position
Growing utility with room for optimization
User Engagement
Documented reach suggests active user community
Technical Stack
Modern tech stack aligned with sponsor technologies

Recommendations to Increase Usefulness Score

Document User Growth

Provide specific metrics on user acquisition and retention rates

Showcase Revenue Model

Detail sustainable monetization strategy and current revenue streams

Expand Evidence Base

Include testimonials, case studies, and third-party validation

Technical Roadmap

Share development milestones and feature completion timeline