sparql-llm
Active·★ 111·MIT·Updated 2026-05-19
★ Trending★ RAG / Knowledge Base
🦜✨ Chat system, MCP server, and reusable components to improve LLMs capabilities when generating SPARQL queries
SPARQL-LLM provides tools to empower Large Language Models (LLMs) to generate accurate SPARQL queries for specific endpoints. It integrates Retrieval-Augmented Generation (RAG) and SPARQL query validation against endpoint schemas to ensure relevant and precise query generation on large-scale knowledge graphs.
#LLM#SPARQL#Knowledge Graph#RAG#Query Generation#Semantic Web#Python#Chatbot
01
Features
01Metadata Extraction from SPARQL Endpoints
02Automated SPARQL Query Validation
03MCP Server with LLM Tools
04Containerized, Deployable Chat System for SPARQL Generation
02
Compatibility
Python
Runtime
Verified via docs
Docker
Deployment
Verified via docs
03
Quick start
1
$ pip install sparql-llm
04
Use cases
↳Build LLM-powered chat services for knowledge graphs.
↳Integrate SPARQL query generation into custom applications.
↳Enable LLMs to query biodata resources via MCP server.
↳Validate SPARQL queries against endpoint metadata.
05
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Comments
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- HHayden NguyenApr 15, 2026
Works with SPARQL endpoints for standard linked data queries.
- OOakley WhiteApr 6, 2026
SPARQL-capable LLM system for querying knowledge graphs through natural language.
- AAvery LewisApr 2, 2026
Good for semantic web developers who want AI assistance with SPARQL queries.
- EEllis ClarkMar 24, 2026
MCP server makes SPARQL capabilities accessible from AI coding workflows.