Summary

This project addresses the challenge of tracking the rapidly evolving AI ecosystem by automating the aggregation and dissemination of key developments. It targets engineers, researchers, and power users by providing daily, weekly, and monthly bilingual digests of AI CLI tools, agent frameworks, official announcements, and trending repositories, accessible via GitHub Issues, Markdown files, a web UI, and an RSS feed.

How It Works

A GitHub Actions workflow runs daily, collecting data from diverse sources: AI CLI tool repositories, OpenClaw and peer AI agent projects, official Anthropic/OpenAI websites (scraped incrementally via sitemaps), GitHub's trending AI repositories, and top AI stories from Hacker News. Processed data includes PRs, issues, trending repo classifications, and community sentiment. Outputs are bilingual (Chinese/English) digests published as GitHub Issues and committed Markdown files, complemented by a dark-themed Web UI and an RSS feed. An MCP server exposes this data for AI clients.

Quick Start & Requirements

Setup involves forking the repository, optionally customizing config.yml for tracked sources, and adding required secrets (e.g., OPENAI_API_KEY) to GitHub Actions settings. Local execution requires pnpm and setting environment variables. The first run may take longer due to initial web content fetching.

• Primary Install/Run: GitHub Actions workflow (automated) or pnpm start (local).
• Prerequisites: pnpm, OpenAI API Key.
• Links: Web UI: https://gsscsd.github.io/big_model_radar, RSS: https://gsscsd.github.io/big_model_radar/feed.xml, Telegram: t.me/agents_radar.

Highlighted Details

• Comprehensive daily, weekly, and monthly AI ecosystem reporting.
• Bilingual (ZH/EN) digests and Web UI.
• Model Context Protocol (MCP) server integration for direct querying by AI clients like Claude Desktop and OpenClaw.
• Configurable data sources via config.yml without code modification.
• Incremental web content scraping for Anthropic and OpenAI news.

Maintenance & Community

No specific maintainer details, sponsorships, or partnerships are listed in the provided text. Community engagement is facilitated via a Telegram channel (t.me/agents_radar).

Licensing & Compatibility

The repository's license is not explicitly stated in the provided README content. This omission requires clarification for adoption. The project is designed for integration with AI clients via the Model Context Protocol (MCP).

Limitations & Caveats

Core functionality relies on an OpenAI API key, potentially incurring usage costs. The absence of a stated license is a significant blocker for determining commercial use or derivative works compatibility. Web scraping is dependent on the stability of target websites' structures.