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Memgraph to Offer a Unique Toolkit for Non-Graph Users to Jumpstart Their Journey to Full GraphRAG AI Capability

via Business Wire
  • New AI Graph Toolkit makes it 10x easier to port SQL and unstructured data into a knowledge graph
  • Developers accelerate access to GraphRAG to meet business users’ demands for accurate ChatGPT-style queries against their organization’s own rich business context
  • Complemented by the MCP (Model Context Protocol) client, the combination makes advanced AI-driven knowledge retrieval easier and more accessible than ever for developers and enterprises new to graph technology

 

Memgraph, the leader in open-source in-memory graph databases purpose-built for dynamic, real-time enterprise applications, is today announcing two new tools specifically architected to open up the power of Retrieval-Augmented Generation based on graph technology (GraphRAG), to the entire database market, so democratizing GraphRAG access.

These include:

  • An immediately available AI Graph Toolkit—a set of open source libraries and utilities that automate the porting of both SQL and unstructured data into a knowledge graph in Memgraph, making it accessible to a chatbot running a GraphRAG pipeline.
  • Later this month—an MCP Client, within Memgraph Lab, that is fully compatible with the emerging standard for context engineering

Together, these products—Unstructured2Graph and SQL2Graph—will deliver more than 10x faster application development for fully GraphRAG-enabled AI business applications, based on results from multiple beta test sites.

Since its introduction by Microsoft in 2024 as a way to address the limitations of large language models, GraphRAG has emerged as a leading method for focusing LLM reasoning and delivering accurate, non-hallucinatory answers to natural language front-end or chatbot queries.

However, adoption beyond the graph community has been challenging, as many developers remain entrenched in the non-graph, SQL-based ecosystem. Compounding this, most of the world’s information is still in non-graph formats: relational databases made up over 62% of global DBMS revenue in 2023, while Gartner estimates 80–90% of new enterprise data is unstructured, locked in everything from text files to PDFs.

Until now, getting SQL and unstructured data into a graph format ready to be used by various search techniques and algorithms within a GraphRAG pipeline has been laborious, error-prone, and inexact. Essentially, for SQL data, this required mapping tables, identifying entities, and performing entity resolution to “graphify” the structures. For unstructured data, it involved chunking, cleaning, and creating vector embeddings, to reach the natural language/ChatGPT interfaces wanted.

With the Memgraph Toolkit and MCP client, engineering teams can bypass the intensive manual coding, programming, and data translation typically required to prepare multiple sources for GraphRAG algorithms. Engineers will still need to fine-tune the final output, but the tedious work of extracting and transforming data from SQL and unstructured formats is already taken care of.

Memgraph’s Chief Technology Officer and Co-founder, Marko Budiselić, says:

“Today, we’re announcing the introduction of two powerful new tools to help engineering teams get started on their GraphRAG journey—making it easier for your AI applications to deliver the answers you need with as little time wasted or hallucinations as possible.

“The AI Graph Toolkit does that by making it extremely easy for developers to transform SQL and unstructured data into knowledge graphs, and then produce GraphRAG-level data structures to superpower your AI chatbot capabilities.

“This makes achieving GraphRAG AI capability and advanced AI-driven knowledge super straightforward for SQL and non-graph experts. Even better, it means you can now run GraphRAG against the ideal back-end LLM input of relational data tables with numeric values and all the business context currently trapped in unstructured text, PDF, and document forms.

“Engineering teams will be able to much more easily unleash the power of graph and GraphRAG across multiple forms of business data, enabling chatbot natural language access and querying capabilities to the whole corporate back end.”

The new Memgraph AI Toolkit is available for download through Github and can be used via Memgraph Cloud.

Finally, Memgraph has launched the JumpStart Programme—a fixed-scope path to a production-ready GraphRAG pipeline in weeks. The package pairs a Memgraph Enterprise license with 20+ hours of hands-on help and implementation, powered by the Memgraph AI Toolkit. Enterprises can expect hybrid search (vector + graph reasoning), sub-second latency, and explainable answers with full provenance. Learn more and sign up here

The Toolkit will be complemented by the MCP client, available later this month, designed to make it easy to connect Memgraph’s graph capabilities to multiple back-end data sources through other MCP Servers, while supporting adoption of an industry standard to accelerate developer AI productivity.

More details about both the Toolkit and the MCP client will be revealed at Connected Data London, taking place at the Leonardo Royal London Hotel Tower Bridge , 20–21 November 2025.

For more technical information and background, read our blog.

Notes to Editors: What is GraphRAG?

According to Gartner® in its Hype CycleTM For AI in Software Engineering 2024 report, "RAG techniques in an enterprise context suffer from problems related to the veracity and completeness of responses caused by limitations in the accuracy of retrieval, contextual understanding, and response coherence. KGs (Knowledge Graphs), a well-established technology, can represent data held within documents and the metadata relating to the documents. Combining both aspects allows RAG applications to retrieve text based on the similarity to the question and contextual representation of the query and corpus, improving response accuracy."

Gartner, Hype Cycle for AI in Software Engineering, 2024, By Adrian Leow, Deepak Seth, Soyeb Barot, 29 July 2024. GARTNER and Hype Cycle are registered trademarks of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.

About Memgraph

Memgraph is a high-performance, in-memory graph database that serves as a real-time context engine for AI applications, powering enterprise solutions with richer context, sub-millisecond query performance, and explainable results that developers can trust. Delivering deep insight, accurate answers, and real-time reasoning at scale across domains from cybersecurity and finance to biotech and knowledge-heavy industries, Memgraph is used by a thriving open-source community of 150,000 members and a customer base that includes industry leaders such as NASA, Cedars-Sinai, and Capitec Bank. To find out more, visit memgraph.com

Unstructured2Graph and SQL2Graph will deliver more than 10× faster application development for fully GraphRAG-enabled AI business applications

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