Memgraph AI Toolkit: A Codebase for Graph-Powered Applications

The Memgraph AI Toolkit is a comprehensive solution designed to enhance the integration of large language models (LLMs) with graph databases, enabling developers to create sophisticated, agent-based workflows using tools like LangGraph and the Model Context Protocol (MCP). The toolkit includes the Memgraph Toolbox, a collection of reusable Python-based tools adhering to the DRY principle, which can execute tasks such as running Cypher queries and calculating graph algorithms. The toolbox facilitates autonomous decision-making by LLM-powered agents on which tools to use, promoting seamless interactions within graph databases like Memgraph. The Memgraph AI Toolkit, now open-source and available on GitHub, consolidates the Memgraph LangChain integration and MCP server into a single monorepo, simplifying the maintenance of shared tools across different frameworks. With a growing list of supported tools, the toolkit supports various operations, such as inspecting storage details, reviewing database constraints, and computing graph metrics like betweenness centrality and PageRank. The Memgraph community encourages feedback and contributions from developers building LangGraph workflows, graph-native RAG pipelines, or agent-based systems, fostering collaboration through platforms like Discord.