by sib-swiss · MCP Server · ★ 109
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✨ SPARQL query generation with LLMs 🦜 This project provides tools to enhance the capabilities of Large Language Models (LLMs) in generating SPARQL queries for specific endpoints: a complete chat web service available at expasy.org/chat a MCP server exposing tools at chat.expasy.org/mcp reusable components published as the pip package The system integrates Retrieval-Augmented Generation (RAG) and SPARQL query validation through endpoint schemas, to ensure more accurate and relevant query generation on large scale knowledge graphs. The components are designed to work either independently or as part of a full chat-based system that can be deployed for a set of SPARQL endpoints. It requires endpoints to include metadata such as SPARQL query examples and endp
| Stars | 109 |
| Forks | 18 |
| Language | Jupyter Notebook |
| Category | MCP Server |
| License | MIT |
| Quality Score | 70.9227787213943/100 |
| Open Issues | 3 |
| Last Updated | 2026-05-19 |
| Created | 2024-05-15 |
| Platforms | mcp |
| Est. Tokens | ~1754k |
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sparql-llm is 🦜✨ Chat system, MCP server, and reusable components to improve LLMs capabilities when generating SPARQL queries. It is categorized as a MCP Server with 109 GitHub stars.
sparql-llm is primarily written in Jupyter Notebook. It covers topics such as expasy, llm, mcp.
You can find installation instructions and usage details in the sparql-llm GitHub repository at github.com/sib-swiss/sparql-llm. The project has 109 stars and 18 forks, indicating an active community.
sparql-llm is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to sparql-llm on Agent Skills Hub include open-ontologies, ontosphere. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.