AlexAI-MCP

AlexAI-MCP / langent

Public

Personal Ontology & 3D Knowledge Nebula

24
7
89% credibility
Found Feb 21, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Langent is an open-source framework that ingests documents from a workspace folder, enables semantic search and agent workflows, and visualizes knowledge as an interactive 3D nebula.

How It Works

1
🔍 Discover Langent

You stumble upon Langent, a magical tool that turns your everyday documents into an interactive 3D universe of knowledge.

2
📁 Prepare Your Folder

Gather your notes, PDFs, texts, and files into one simple folder on your computer.

3
🚀 Start the Magic

Click to launch and let it wake up your knowledge base with a few easy steps.

4
📥 Absorb Your Files

It scans your folder and pulls in all your information, creating a sparkling cloud of ideas.

5
🌌 Enter the Nebula

Open your web browser to see your documents swirling as a beautiful 3D galaxy you can fly through.

6
🔍 Search and Chat

Type any question to light up connections, zoom into spots, and talk to helpful guides for answers.

✨ Discover Hidden Gems

You now explore your world of info like a space adventurer, uncovering insights and links effortlessly.

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Star Growth

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AI-Generated Review

What is langent?

Langent turns your document workspace into a searchable knowledge nebula: drop in Markdown, PDFs, or CSVs, and it ingests them into a vector store for semantic search, optionally links to a Neo4j graph for structured ontology, and renders everything as an interactive 3D visualization. Built in Python with LangChain for RAG agents, FastAPI for API/CLI/WebSocket serving, and Three.js for the nebula view, it also exposes MCP tools for host AI integration without API keys. Perfect for andrew brenner personal ontology setups or langental-style personal knowledge bases.

Why is it gaining traction?

The 3D nebula viz stands out—watch your docs cluster in space, search to highlight clusters, and fly through results—while workspace file watching auto-ingests changes. MCP server hooks into tools like Antigravity or Claude without personal GitHub Copilot licenses, and hybrid vector-graph queries beat plain RAG. Devs dig the zero-config CLI (langent ingest, langent serve) for quick personal GitHub repositories or langenthal schweiz project wikis.

Who should use this?

AI tinkerers building personal ontologies from scattered notes, like langenthal trendelburg researchers mapping domain knowledge. Devs managing personal GitHub accounts for work, needing visual RAG over code/docs without setup hassle. Ontology enthusiasts tracking langenthal porzellan or langenthal schnitzel data in a langenthonhausen-style graph.

Verdict

Worth a spin for the nebula viz alone if you run Neo4j and want MCP agent tools, but with 18 stars and 0.8999999761581421% credibility score, it's early-stage—expect rough edges in docs and tests. Prototype your personal GitHub page knowledge base today; production needs polishing.

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