graphrag-toolkit MCP Server
awslabs/graphrag-toolkit
[](https://agentrank-ai.com/tool/awslabs--graphrag-toolkit/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Python toolkit for building graph-enhanced GenAI applications
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
awslabs/graphrag-toolkit is a Python tool licensed under Apache-2.0. Python toolkit for building graph-enhanced GenAI applications Topics: amazon-neptune, graph-database, graphrag, llama-index, amazon-opensearch-serverless, mcp, postgresql.
Ranked #455 out of 81417 indexed tools.
In the top 1% of all indexed tools.
Has 36 contributors.
Actively maintained with commits in the last week.
Ecosystem
Score Breakdown
445 stars → growing community
Last commit 1d ago → actively maintained
111/149 issues closed → decent issue management
36 contributors → active community
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
Matched Queries
From the README
## GraphRAG Toolkit > Check out the graphrag-toolkit Docs found here: [Start here!](https://awslabs.github.io/graphrag-toolkit/) The graphrag-toolkit is a collection of Python tools for building graph-enhanced Generative AI applications. ### Lexical Graph The [lexical-graph](https://github.com/awslabs/graphrag-toolkit/tree/main/lexical-graph) provides a framework for automating the construction of a [hierarchical lexical graph](https://awslabs.github.io/graphrag-toolkit/lexical-graph/graph-model/) from unstructured data, and composing question-answering strategies that query this graph when answering user questions. #### Additional Resources - [Introducing the GraphRAG Toolkit](https://aws.amazon.com/blogs/database/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](https://www.youtube.com/watch?v=KD5C93kwBMg) [Video] Discusses the design of tRead full README on GitHub →
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