Kwipu

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Kwipu turns a folder of documents into a property-graph RAG index that you can explore and query from an interactive terminal, a 3D web interface, or an MCP client. It works with ordinary knowledge folders and Obsidian-style vaults.

About “fully local”: Kwipu can run fully locally when you select a local Ollama LLM and embedding model. The intentional default LLM is gpt-oss:20b-cloud, which can send document chunks, retrieved context, and questions to its provider. Choose cloud or local before indexing.

Choose your path

I want to…	Start here
Ask my notes directly in a terminal	Terminal-only use
Explore the graph and ask from a browser	Quick start: web UI
Use my own notes or Obsidian vault	Use your own document folder
Connect an AI client over MCP	MCP server
Configure or deploy the system	Configuration reference
Run tests or contribute code	Developer setup

What Kwipu does

• Builds a property graph from .md, .txt, .pdf, and .docx documents.
• Extracts semantic relations with an LLM and structural relations from wikilinks and YAML frontmatter.
• Combines vector similarity, BM25, temporal metadata, and optional synonym retrieval.
• Grounds answers in source chunks and returns citations.
• Visualizes entities, documents, and relations in an interactive 3D graph.
• Watches the source folder and updates persisted storage safely.
• Supports English, Italian, French, German, Spanish, and Portuguese patterns.
• Exposes the same knowledge through the terminal, web API, and MCP.

Web interface

1. Ask a grounded question and open its sources

2. Reconstruct changes across meetings and reviews

3. Compare people, roles, and supporting documents

Terminal interface

Use Kwipu directly from the command line while keeping your notes open in Obsidian. The terminal returns grounded answers from the graph and continues watching the knowledge folder for changes.

Ask about roles, tasks, and project context

Query meeting decisions and rebuild after note changes

For installation and commands, see Terminal-only use.

Choose cloud or local

Kwipu connects to an Ollama-compatible endpoint, which defaults to http://localhost:11434. A local endpoint does not by itself guarantee local model execution.

Mode	LLM	Data behavior	Before first use
Cloud default	gpt-oss:20b-cloud	Ollama can forward context and questions to the model provider. Review that provider's privacy, retention, and data-location policies.	ollama pull gpt-oss:20b-cloud
Local example	qwen2.5:7b	Inference remains on the machine when both models and the Ollama endpoint are local.	ollama pull qwen2.5:7b

Both modes use the local embedding model in the default configuration:

ollama pull nomic-embed-text

A remote Ollama endpoint sends data to that host. Kwipu requires HTTPS for non-loopback endpoints unless insecure HTTP is explicitly enabled for a trusted network.

Quick start: web UI