chenlinyang/alg-mcp

Stars Lighting, enabling intelligent querying based on the RAG+MCP dual-engine architecture.

31
/ 100
Emerging

This project helps businesses and teams answer complex questions about their vast datasets using natural language. You can input questions like "What were the sales figures for Q3 in the western region, grouped by product category?" and receive precise, structured data queries and results. It's designed for data analysts, product designers, or technical researchers who need to quickly extract insights from large internal databases without writing code.

No commits in the last 6 months.

Use this if you need to perform data retrieval and analysis on thousands of data directories and billions of data facts by simply asking questions in plain language.

Not ideal if your data is small, unstructured, or you primarily need to perform tasks outside of querying structured databases and external APIs.

data-analysis business-intelligence technical-research product-design database-querying
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 7 / 25
Maturity 15 / 25
Community 7 / 25

How are scores calculated?

Stars

27

Forks

2

Language

Java

License

MIT

Category

mcp-rag-servers

Last pushed

Apr 18, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/rag/chenlinyang/alg-mcp"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.