andyliszewski/grounding-ai

Overview

Local-first document corpus pipeline for grounding AI agents. It is a Python package that turns input documents into a reference corpus. The pipeline prioritizes keeping data on the local machine.

Best for

Best for
Developers building Python-based grounded AI agents that need a local-first document pipeline

Use cases

• Indexing company documentation for an AI assistant
• Preparing a personal corpus for retrieval-augmented generation
• Creating an on-device reference repository for agent workflows

Notes

Local-first document corpus pipeline for grounding AI agents. It is a Python package that turns input documents into a reference corpus. The pipeline prioritizes keeping data on the local machine.

1 stars on GitHub. Last updated 2026-06-05. Licensed MIT.

Use cases

• Indexing company documentation for an AI assistant
• Preparing a personal corpus for retrieval-augmented generation
• Creating an on-device reference repository for agent workflows

Pros

• Local-first design helps keep private documents under your control
• Python implementation fits well into existing agent tooling
• Narrow focus on corpus construction keeps the codebase simple

Cons

• Only 1 star on GitHub indicates very limited community adoption
• Vendor is listed as Various so clear support and maintenance are unclear
• Description covers the corpus only, with no details on retrieval or agent integration

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.