mlsanityData to 7 Oct 2026

Agentic SPARQL: Evaluating SPARQL-MCP-powered Intelligent Agents on the Federated KGQA Benchmark

arXiv 2603.06582 ↗First posted 20 Jan 2026cs.IR cs.AI cs.MAcited by 3

On the map: LLM agents and tool use → Web, search, and research agents

Abstract (arXiv)

Standard protocols such as the Model Context Protocol (MCP) that allow LLMs to connect to tools have recently boosted "agentic" AI applications, which, powered by LLMs' planning capabilities, promise to solve complex tasks with the access of external tools and data sources. In this context, publicly available SPARQL endpoints offer a natural connection to combine various data sources through MCP by (a) implementing a standardised protocol and query language, (b) standardised metadata formats, and (c) the native capability to federate queries. In the present paper, we explore the potential of SPARQL-MCP-based intelligent agents to facilitate federated SPARQL querying: firstly, we discuss how to extend an existing Knowledge Graph Question Answering benchmark towards agentic federated Knowledge Graph Question Answering (FKGQA); secondly, we implement and evaluate the ability of integrating SPARQL federation with LLM agents via MCP (incl. endpoint discovery/source selection, schema exploration, and query formulation), comparing different architectural options against the extended benchmark. Our work complements and extends prior work on automated SPARQL query federation towards fruitful combinations with agentic AI.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 19 of its 49 references that are in the map. First posted on arXiv 20 Jan 2026.

Builds on

19 of 49 references.

References · 19

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  3. 2025Qwen3 Technical Reportcited by 8,195
  4. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,779
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7 more
  1. 2025A Survey on Large Language Models with some Insights on their Capabilities and Limitationscited by 41
  2. 2022Modern Baselines for SPARQL Semantic Parsingcited by 34
  3. 2024LLM-based SPARQL Query Generation from Natural Language over Federated Knowledge Graphscited by 22
  4. 2025GRASP: Generic Reasoning And SPARQL Generation across Knowledge Graphscited by 7
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  7. 2018Heuristics-based Query Reordering for Federated Queries in SPARQL 1.1 and SPARQL-LDcited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026Making Mathematical Knowledge Explainable, Accessible and Interoperable Through Large Language Model Integrationcited by 0
  2. 2026Enabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN)cited by 0
  3. 2026Natural Language Knowledge Graph Query Execution: Leveraging Controlled Semantics in the LLM Context Windowcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026KGVoyager: Knowledge Graph Agnostic Question Answering via Agentic Navigation
  2. 2026Towards Researcher Agents for Knowledge-Graph Question Answering
  3. 2025From Graph Retrieval to Schema Realization: Counterfactual Validation for Text-to-SPARQL over Heterogeneous Knowledge Graphs
  4. 2025Learning to Refine: An Agentic RL Approach for Iterative SPARQL Query Construction
  5. 2026MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQA
  6. 2025Text-to-SPARQL Goes Beyond English: Multilingual Question Answering Over Knowledge Graphs through Human-Inspired Reasoning
  7. 2025ARUQULA -- An LLM based Text2SPARQL Approach using ReAct and Knowledge Graph Exploration Utilities
  8. 2025ARK-V1: An LLM-Agent for Knowledge Graph Question Answering Requiring Commonsense Reasoning