sample-okf-llm-wiki
Active·★ 33·MIT-0·Updated 2026-10-21
Data Wiki converts AWS data sources like Glue Data Catalog and Redshift into portable, AI-authored knowledge bundles, making complex data semantics accessible to AI agents. It uses LLMs to generate markdown documentation for datasets, including tables, joins, and metrics, and serves these via the Model Context Protocol (MCP).
#AWS#LLM#RAG#Knowledge Base#Data Catalog#AI Agents#Model Context Protocol#Terraform
01
Features
01Automated Induction: AI agents author knowledge bundles from source catalogs.
02Pluggable Data Sources: Supports AWS Glue and Amazon Redshift, with extensible architecture.
03Self-Healing Freshness: Automatically re-harvests on Glue catalog changes and keeps search index in sync.
04Served Over MCP: Enables agents to discover, read, and semantically search bundles via the Model Context Protocol.
05Web Console: Provides a React UI for managing datasets, harvests, and browsing bundles.
02
Compatibility
AWS Glue Data Catalog
Data Source
Verified via docs
Amazon Redshift
Data Source
Verified via docs
Amazon Bedrock
LLM/Embedding
Verified via docs
Amazon Bedrock AgentCore Runtime
Agent Runtime
Verified via docs
Python
Runtime
Verified via docs
Terraform
Deployment
Verified via docs
03
Quick start
1
$ git clone https://github.com/okf/sample-okf-llm-wiki.git
2
$ cd sample-okf-llm-wiki
3
$ ./scripts/deploy.sh
04
Use cases
↳Enabling AI agents to understand complex AWS data semantics.
↳Automated generation and synchronization of data documentation.
↳Providing semantic search and QA capabilities over enterprise data.
↳Integrating structured data knowledge into LLM applications via MCP.
↳Benchmarking and improving text-to-SQL agent accuracy.
05
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