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grahamrowe82/pt-edge

· github.com/grahamrowe82/pt-edge

source AI projects across GitHub, PyPI, npm, HuggingFace, Docker Hub, and Hacker News. 47 MCP tools for discovery, comparison, trend analysis, and semantic search across AI repos, HuggingFace models/datasets, and public APIs.

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Scored 6 months ago · breakdown

About grahamrowe82/pt-edge

grahamrowe82/pt-edge is an MCP server in the Search category: source AI projects across GitHub, PyPI, npm, HuggingFace, Docker Hub, and Hacker News. 47 MCP tools for discovery, comparison, trend analysis, and semantic search across AI repos, HuggingFace models/datasets, and public APIs.

Install

From source
git clone https://github.com/grahamrowe82/pt-edge

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

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README

PT-Edge — AI Infrastructure Intelligence

PT-Edge is a precomputed reasoning cache for AI infrastructure decisions. It tracks 220,000+ AI repos across GitHub, PyPI, npm, Docker Hub, HuggingFace, and Hacker News, scores them daily on quality, and publishes the results as a 220,000+ page directory site.

The site serves two audiences: AI agents reading pages on behalf of humans (structured, front-loaded, machine-readable) and humans reading directly (navigable, trustworthy, original analysis). Every page is designed so an AI agent can land on it and walk away with a confident, citable recommendation in one pass.

Every major AI lab's crawl infrastructure treats the site as a primary data source. The access logs are themselves an intelligence layer — see Demand Radar below.

Directory site: mcp.phasetransitions.ai — 220,000+ pages across 17 domains with 2,400+ categories, updated daily.

Built by Graham Rowe

How It Works

  1. Ingest — daily pipeline pulls GitHub stats, package downloads, releases, HN posts, HuggingFace models/datasets, and registry data
  2. Score — composite quality score (0-100) from four dimensions: maintenance, adoption, maturity, community
  3. Enrich — LLM-generated technical summaries, practitioner-focused assessments, and comparison analyses from READMEs
  4. Publish — static site generation across 17 domains with structured data, internal linking, and freshness signals
  5. Observe — bot traffic analysis reveals what the AI ecosystem values (Demand Radar)

The entire system runs on a single server instance for under $300/month.

Quality Scoring

Dimension Max Signals
Maintenance 25 Commit activity (30d), push recency
Adoption 25 Stars (log scale), monthly downloads, reverse dependents
Maturity 25 License, PyPI/npm packaging, repo age
Community 25 Forks (log scale), fork-to-star ratio

Tiers: Verified (70-100), Established (50-69), Emerging (30-49), Experimental (10-29)

Demand Radar

Every bot hit on the site is latent intelligence. The access logs carry three layers of signal:

  • Indexing bots (Meta, Anthropic, Amazon, Google, Perplexity, OpenAI) — what AI companies think will be valuable in future model weights. Each bot has a distinct crawl strategy that reveals its parent company's priorities.
  • User-action bots (ChatGPT-User, OAI-SearchBot, Perplexity-User) — what real humans are asking AI right now. Each hit represents a practitioner making a technology decision through an AI intermediary.
  • Human visitors — what people find through search engines directly.

The Demand Radar extracts these signals and feeds them into content prioritisation — eventually via trained ML models rather than hand-tuned weights. See scratch/demand-radar/ for the full analysis.

Stack

Python, FastAPI, PostgreSQL + pgvector, LLM enrichment (multiple providers), static site generation via Jinja2 + Tailwind CSS. Hosted on Render. MCP tools and REST API for programmatic access.

Development

This is a production system with no staging environment. The database is a live 1GB+ PostgreSQL instance — queries hit real data. See docs/development.md for setup notes and safety rules.

Documentation

License

MIT — see LICENSE.

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About grahamrowe82/pt-edge

How do I install grahamrowe82/pt-edge?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is grahamrowe82/pt-edge safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is grahamrowe82/pt-edge still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.