How do I test if the API is running?
Make a GET request to `https://api.valgresky.com/gres/health`. No authentication is required, and it returns `{ "Gres Check": "ok" }`.
@valgresky
基本情報
Gres is a minimalist AI command server for agents and developers. Snap pages, grab sites, source docs, and ask anything. One interface, zero fluff.
ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
Gres API is an agentic endpoint layer built with FastAPI, offering modular tools, secure key authentication, and production-ready Docker deployment. It provides endpoints for snapping web pages, crawling sites or sitemaps, listing indexed sources, and querying a vector index via RAG (Retrieval-Augmented Generation).
Set your API key in a .env file as VALGRESKY_API_KEY=sk_valgresky_yourkeyhere. The base URL is https://api.valgresky.com. Use the health check endpoint without authentication (/gres/health). All other endpoints require an X-API-Key header. Invoke endpoints like /gres/snap, /gres/grab, /gres/source, and /gres/ask with appropriate JSON payloads.
/gres/snap/gres/grab/gres/source/gres/askMake a GET request to `https://api.valgresky.com/gres/health`. No authentication is required, and it returns `{ "Gres Check": "ok" }`.
All main API endpoints require an `X-API-Key` header. Set your key in a `.env` file as `VALGRESKY_API_KEY=sk_valgresky_yourkeyhere` and include it in every request.
Four authenticated endpoints: `/gres/snap` (snap a page), `/gres/grab` (crawl a site or sitemap), `/gres/source` (list indexed sources), and `/gres/ask` (query the vector index with RAG). Plus a public health check at `/gres/health`.
Yes. A Docker Compose file is provided that builds the service, exposes port 8051, mounts required directories, and sets environment variables like `OPENAI_API_KEY` and `GRES_EMBEDDINGS_PATH`.
The server includes a shared MCP (Model Context Protocol) instance in `/src/tools/mcp.py`. Tools like `snap` are decorated with `@mcp.tool` and can be invoked as MCP tools, enabling integration with AI agents.
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