openGlad
openGlad is an MCP server that provides AI agents with tools for loss-prevention, market intelligence, and startup diagnostics using data from Reddit, Hacker News, GitHub, and Polymarket.
README
<p align="center"> <img src="github/opengladlogo.png" alt="openGlad Logo" width="250" /> <p align="center"><strong>The Loss-Prevention Friction Engine for Founders</strong></p> <p align="center"> An AI-powered MCP server that stops you from building things nobody wants using clinical analytics, behavioral pattern scanning, and real-time market intelligence from Reddit, Hacker News, GitHub, and Polymarket. </p> <p align="center"> <a href="#tools">Tools</a> β’ <a href="#quickstart">Quickstart</a> β’ <a href="#architecture">Architecture</a> β’ <a href="#deployment">Deployment</a> </p> </p>
<p align="center"> <img src="github/openGladDemo.gif" alt="openGlad Demo" style="max-width: 100%;" /> </p>
What is openGlad?
openGlad is a Model Context Protocol (MCP) server that acts as the ultimate friction engine for startups. It provides AI agents (Claude, Cursor, Windsurf, Le Chat, etc.) with specialized tools to enforce loss-prevention before you write a single line of code:
- π Loss-Prevention Pipeline β Runs behavioral pattern scans, 3-scenario failure predictions, and locks building until monetization is confirmed.
- π Multi-Source Market Intelligence β Aggregates real-time data from Reddit (11+ subreddits), Hacker News, GitHub, and Polymarket prediction markets to detect overcrowding and entry risks.
- βοΈ Comparative Friction Analysis β Runs parallel market intelligence on 2-3 ideas simultaneously and returns a ranked verdict on which one (if any) is worth pursuing.
- π Startup Diagnostics β Evaluates execution stability, revenue health, burnout risk, and distribution discipline.
- π©Ί Clinical Triage β Objective, data-driven assessments with zero motivational fluff.
Think of it as an anti-delusion engine for your startup β designed to tell you 'no' before you waste months building the wrong thing.
Architecture
ββββββββββββββββ βββββββββββββββββββββββββββββββββ
β AI Client β MCP β openGlad Worker β
β (Claude, βββββββββΊβ (Cloudflare Edge) β
β Cursor, β β Version 5.0 β
β Windsurf) β βββββββββββββββ¬ββββββββββββββββββ
ββββββββββββββββ β Parallel fetch (cached 1hr)
ββββββββββββββΌβββββββββββββ
ββββββββΌβββββββ ββββΌβββββ βββββββΌβββββββ ββββββββΌβββββββ
β Reddit β β HN β β GitHub β β Polymarket β
β 11+ subs β βAlgoliaβ β Public API β β Gamma API β
β + topic exp.β β free β β no key β β free β
βββββββββββββββ βββββββββ ββββββββββββββ βββββββββββββββ
Tech Stack:
- Runtime: Cloudflare Workers (edge-deployed, globally distributed)
- Protocol: MCP (Model Context Protocol) via Streamable HTTP
- Market Data: Reddit + Hacker News (Algolia) + GitHub + Polymarket (all free, no API keys)
- Language: TypeScript (Modular Architecture)
Tools
π§ Friction Engine (Loss Prevention)
| Tool | Description | Market Data |
|---|---|---|
run_the_bet |
Mega-pipeline combining Pattern Scan, Loss Simulation, and Revenue Gate. Start here for new ideas. | Reddit + HN + GitHub + Polymarket |
pattern_scan |
Detects behavioral risk patterns (overbuilding drift, monetization avoidance, prestige bias). | None |
loss_simulation |
Generates 3-scenario failure predictions (best, likely, worst) with quantified expected loss. | Reddit + HN + GitHub + Polymarket |
revenue_gate |
Locks building until clear monetization strategy is confirmed. Produces unlock tasks. | None |
compare_ideas |
Parallel multi-source analysis of 2-3 ideas with ranked comparison and single verdict. | Reddit + HN + GitHub + Polymarket |
π Market Intelligence (Multi-Source)
| Tool | Description | Market Data |
|---|---|---|
analyze_market_trends |
Overcrowding & entry risk filter. Detects tarpit ideas and late entry risks. | Reddit + HN + GitHub + Polymarket |
scan_reddit_trends |
Broad trend scanner: sentiment, red flags, cautionary tales, and 6-12 month predictions. | Reddit + HN + GitHub + Polymarket |
Data Sources:
| Source | API | What it adds |
|---|---|---|
| Public JSON (free, no key) | Community sentiment, 11 base subreddits + dynamic topic expansion | |
| Hacker News | Algolia API (free, no key) | Technical founder signal β developer adoption, HN discussions |
| GitHub | Public Search API (free, no key) | Competitor repo activity, star velocity, open source adoption |
| Polymarket | Gamma API (free, no key) | Prediction market odds β real money bets on outcome probabilities |
Reddit subreddits (base): r/Startup_Ideas Β· r/Business_Ideas Β· r/SaaS Β· r/SideProject Β· r/EntrepreneurRideAlong Β· r/IndieHackers Β· r/Futurology Β· r/Technology Β· r/AINewsAndTrends Β· r/Startups Β· r/Entrepreneur
Dynamic expansion adds topic-specific subreddits (e.g. r/MachineLearning for AI queries, r/CryptoCurrency for crypto, r/fintech for finance).
π©Ί Startup Diagnostics
| Tool | Description |
|---|---|
analyze_startup |
Smart triage router. Auto-detects ideas vs metrics and routes accordingly. |
analyze_execution_stability |
Assesses development velocity, engineering risks, and technical debt. |
analyze_revenue_health |
Evaluates MRR/ARR trajectory, financial risks, churn, and unit economics. |
analyze_burnout_risk |
Detects burnout signals from work patterns, cognitive load, and focus entropy. |
analyze_distribution_discipline |
Measures marketing risks, output consistency, and funnel efficiency. |
generate_full_diagnosis |
Comprehensive system scan across all diagnostic dimensions. |
π¬ MCP Prompts
| Prompt | Description |
|---|---|
run-the-bet |
Full loss-prevention pipeline for a new idea. |
market-check |
Market saturation and trend analysis combining broad scan + focused analysis. |
should-i-build |
Quick friction check: pattern scan + revenue gate to determine if building is allowed. |
analyze-startup |
Guided startup analysis β triage and routing for ideas or metrics. |
π MCP Resources
| Resource | URI | Description |
|---|---|---|
| Usage Guide | openglad://guide |
Agent-readable guide with tool selection logic, recommended workflows, and usage tips. |
Quickstart
Connect to the hosted server
The MCP server is deployed and ready to use:
https://openglad.tuguberk.dev/mcp
Claude Desktop / Cursor / Windsurf / Any MCP Client
Add to your MCP client configuration:
{
"mcpServers": {
"openGlad": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://openglad.tuguberk.dev/mcp"]
}
}
}
MCP Inspector (for testing)
npx @modelcontextprotocol/inspector@latest
# Enter URL: https://openglad.tuguberk.dev/mcp
Example Prompts
Once connected, try these with your AI client:
"Run the bet on my startup idea: an AI-powered tool that generates investor pitch decks from a one-page brief"
"Compare these two ideas for me: (1) AI accounting SaaS for freelancers, (2) no-code internal tools builder"
"Run a full health diagnostic on my startup with these metrics: MRR $12k, churn 8%, 3 developers, shipping weekly"
"Is the micro-SaaS market oversaturated? Check trends across Reddit, HN, and GitHub."
Deployment
Prerequisites
Deploy your own
# Clone and install
git clone https://github.com/tugberkakbulut/openGlad.git
cd openGlad
npm install
# Local development
npm run dev
# Deploy to Cloudflare
npx wrangler deploy
No API keys required β openGlad fetches all market data via free public APIs. Results are cached at the edge for 1 hour per query.
Project Structure
openGlad/
βββ src/
β βββ config/
β β βββ constants.ts # Subreddits + dynamic topic expansion map
β βββ prompts/
β β βββ index.ts # LLM system prompts for all tools
β βββ services/
β β βββ aggregator.ts # Multi-source fetcher + evidence envelope wrapper
β β βββ reddit.ts # Reddit search + engagement ranking + dedup + retry
β β βββ hackernews.ts # HN Algolia API integration
β β βββ polymarket.ts # Polymarket Gamma API integration
β β βββ github.ts # GitHub public search API integration
β βββ tools/
β β βββ friction.ts # Friction engine tools (run_the_bet, compare_ideas, etc.)
β β βββ diagnostics.ts # Diagnostic tools (execution, revenue, burnout, distribution)
β βββ utils/
β β βββ dedupe.ts # Jaccard N-gram deduplication + per-author caps + engagement scoring
β β βββ helpers.ts # Evidence envelope response builder
β βββ index.ts # Server entry point, prompts, resources & tool registration
βββ wrangler.jsonc # Cloudflare Worker configuration
βββ package.json
βββ tsconfig.json
How It Works
Friction Engine Flow (Loss-Prevention)
- User asks β "I want to build an AI resume builder"
- AI client β Calls
run_the_betoranalyze_startup - openGlad Worker β Fetches from 4 sources in parallel: Reddit (11+ subreddits), HackerNews, GitHub, Polymarket (all cached 1hr at edge)
- Deduplication & Ranking β Jaccard similarity removes cross-source duplicates; per-author cap (max 3) prevents single-voice dominance; engagement scoring weights freshness + score + activity
- Pattern Scan β Identifies behavioral risks (overbuilding, monetization avoidance)
- Loss Simulation β Maps out 3 failure scenarios with quantified expected loss grounded in real market signals
- Revenue Gate β Locks building until monetization is proven
- User receives β A brutal reality check: blind spots, failure modes, and whether they're allowed to build
compare_ideas Flow
- User provides β 2-3 startup idea descriptions
- Parallel fetch β Market context fetched for all ideas simultaneously
- Comparative analysis β Each idea gets a compressed friction block (pattern risk, market signal, expected loss, gate status)
- Ranked verdict β Single recommendation on which idea (if any) to pursue
Built With
- Cloudflare Workers β Serverless edge computing
- Model Context Protocol β Standard protocol for AI tool integration
- Cloudflare Agents SDK β MCP server framework
- Reddit Public JSON API β Community market intelligence
- Hacker News Algolia API β Developer community signals
- GitHub REST API β Open source adoption & competitor activity
- Polymarket Gamma API β Prediction market odds
Inspiration
Multi-source aggregation, Jaccard deduplication, engagement-based ranking, thin-source retry, and evidence envelope patterns are inspired by mvanhorn/last30days-skill (MIT).
License
MIT
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