Install
$ agentstack add mcp-tuguberk-openglad ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
The Loss-Prevention Friction Engine for Founders
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.
Tools • Quickstart • Architecture • Deployment
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:
- 🛑 Loss-Prevention Pipeline — Runs behavioral pattern scans, 3-scenario failure predictions, and locks building until monetization is confirmed.
- 🔍 Multi-Source Market Intelligence — Aggregates real-time data from Reddit (11+ subreddits), Hacker News, GitHub, and Polymarket prediction markets to detect overcrowding and entry risks.
- ⚔️ Comparative Friction Analysis — Runs parallel market intelligence on 2-3 ideas simultaneously and returns a ranked verdict on which one (if any) is worth pursuing.
- 📊 Startup Diagnostics — Evaluates execution stability, revenue health, burnout risk, and distribution discipline.
- 🩺 Clinical Triage — Objective, data-driven assessments with zero motivational fluff.
> Think of it as an anti-delusion engine for your startup — designed to tell you 'no' before you waste months building the wrong thing.
Architecture
┌──────────────┐ ┌───────────────────────────────┐
│ AI Client │ MCP │ openGlad Worker │
│ (Claude, │◄──────►│ (Cloudflare Edge) │
│ Cursor, │ │ Version 5.0 │
│ Windsurf) │ └─────────────┬─────────────────┘
└──────────────┘ │ Parallel fetch (cached 1hr)
┌────────────┼────────────┐
┌──────▼──────┐ ┌──▼────┐ ┌─────▼──────┐ ┌──────▼──────┐
│ Reddit │ │ HN │ │ GitHub │ │ Polymarket │
│ 11+ subs │ │Algolia│ │ Public API │ │ Gamma API │
│ + topic exp.│ │ free │ │ no key │ │ free │
└─────────────┘ └───────┘ └────────────┘ └─────────────┘
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
🚧 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 |
🔍 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 | |--------|-----|-------------| | Reddit | Public JSON (free, no key) | Community sentiment, 11 base subreddits + dynamic topic expansion | | Hacker News | Algolia API (free, no key) | Technical founder signal — 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 — real money bets on outcome probabilities |
Reddit subreddits (base): r/Startup_Ideas · r/Business_Ideas · r/SaaS · r/SideProject · r/EntrepreneurRideAlong · r/IndieHackers · r/Futurology · r/Technology · r/AINewsAndTrends · r/Startups · r/Entrepreneur
Dynamic expansion adds topic-specific subreddits (e.g. r/MachineLearning for AI queries, r/CryptoCurrency for crypto, r/fintech for finance).
🩺 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. |
💬 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 — triage and routing for ideas or metrics. |
📖 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 — openGlad fetches all market data via free public APIs. Results are cached at the edge for 1 hour per query.
Project Structure
openGlad/
├── src/
│ ├── config/
│ │ └── constants.ts # Subreddits + dynamic topic expansion map
│ ├── prompts/
│ │ └── index.ts # LLM system prompts for all tools
│ ├── services/
│ │ ├── aggregator.ts # Multi-source fetcher + evidence envelope wrapper
│ │ ├── reddit.ts # Reddit search + engagement ranking + dedup + retry
│ │ ├── hackernews.ts # HN Algolia API integration
│ │ ├── polymarket.ts # Polymarket Gamma API integration
│ │ └── github.ts # GitHub public search API integration
│ ├── tools/
│ │ ├── friction.ts # Friction engine tools (run_the_bet, compare_ideas, etc.)
│ │ └── diagnostics.ts # Diagnostic tools (execution, revenue, burnout, distribution)
│ ├── utils/
│ │ ├── dedupe.ts # Jaccard N-gram deduplication + per-author caps + engagement scoring
│ │ └── helpers.ts # Evidence envelope response builder
│ └── index.ts # Server entry point, prompts, resources & tool registration
├── wrangler.jsonc # Cloudflare Worker configuration
├── package.json
└── tsconfig.json
How It Works
Friction Engine Flow (Loss-Prevention)
- User asks → "I want to build an AI resume builder"
- AI client → Calls
run_the_betoranalyze_startup - openGlad Worker → Fetches from 4 sources in parallel: Reddit (11+ subreddits), HackerNews, GitHub, Polymarket (all cached 1hr at edge)
- Deduplication & Ranking → Jaccard similarity removes cross-source duplicates; per-author cap (max 3) prevents single-voice dominance; engagement scoring weights freshness + score + activity
- Pattern Scan → Identifies behavioral risks (overbuilding, monetization avoidance)
- Loss Simulation → Maps out 3 failure scenarios with quantified expected loss grounded in real market signals
- Revenue Gate → Locks building until monetization is proven
- User receives → A brutal reality check: blind spots, failure modes, and whether they're allowed to build
compare_ideas Flow
- User provides → 2-3 startup idea descriptions
- Parallel fetch → Market context fetched for all ideas simultaneously
- Comparative analysis → Each idea gets a compressed friction block (pattern risk, market signal, expected loss, gate status)
- Ranked verdict → Single recommendation on which idea (if any) to pursue
Built With
- Cloudflare Workers — Serverless edge computing
- Model Context Protocol — Standard protocol for AI tool integration
- Cloudflare Agents SDK — MCP server framework
- Reddit Public JSON API — Community market intelligence
- Hacker News Algolia API — Developer community signals
- GitHub REST API — Open source adoption & competitor activity
- Polymarket Gamma API — 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
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: Tuguberk
- Source: Tuguberk/openGlad
- License: MIT
- Homepage: https://openglad.tuguberk.dev
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.