No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by awslabs · MCP Server · ★ 442
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GraphRAG Toolkit The graphrag-toolkit is a collection of Python tools for building graph-enhanced Generative AI applications. Installation instructions and requirements are detailed separately with each tool. Lexical Graph The lexical-graph provides a framework for automating the construction of a hierarchical lexical graph from unstructured data, and composing question-answering strategies that query this graph when answering user questions. Additional Resources Introducing the GraphRAG Toolkit [Blog Post] GraphRAG Toolkit launch blog post. AWS re:Invent 2025 - Deep Dive into Deloitte's Amazon Neptune GenAI Security Intelligence Center [Video] Discusses the design of the GraphRAG Toolkit and shows how Deloitte use the lexical graph in its security intelligence center. VectorDB vs GraphDB for Gen AI Agents [Video] Discussion on the differences between vector search and graph search, how they work, and how to use them together to enhance the accuracy of GenAI applications and more. Includes examples that use the GraphRAG Toolkit. [Leveraging VectorDB and GraphDB: Enhancing Gen AI Applications with Hybrid Queries](https://medium.com/@kwokmeli/leveraging-vectordb-and-graphdb-e
| Stars | 442 |
| Forks | 106 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 60.3779679165634/100 |
| Open Issues | 47 |
| Last Updated | 2026-09-22 |
| Created | 2024-11-15 |
| Platforms | mcp, python |
| Est. Tokens | ~14k |
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graphrag-toolkit is Python toolkit for building graph-enhanced GenAI applications. It is categorized as a MCP Server with 442 GitHub stars.
graphrag-toolkit is primarily written in Python. It covers topics such as amazon-neptune, amazon-opensearch-serverless, graph-database.
You can find installation instructions and usage details in the graphrag-toolkit GitHub repository at github.com/awslabs/graphrag-toolkit. The project has 442 stars and 106 forks, indicating an active community.
graphrag-toolkit is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to graphrag-toolkit on Agent Skills Hub include py-gpt, pg-aiguide, nocturne_memory. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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